The Anatomy of a Good QC Solution
- Krishna Uppuluri, VP Marketing, Interra Systems

As the media transitions from tape-based analog to file-based digital content, the existing workflows and operational methods of media companies will need to be updated. File-based workflows are being widely adopted as mainstream solution by Broadcasters, Post-production houses, IPTV, satellite and archiving companies. A file-based content can be stored on traditional IT infrastructure, modified & analyzed by software and transferred via high-speed networks to Connected-consumers across multiple-screens for increased revenues. The pace and the freedom to change the file-based content can lead to various problems in content. Hence the content needs to be verified after every change. New generations of Quality Control (QC) solutions such as Interra’s Baton fulfill this need to verify the content at every stage. This article discusses the anatomy of a good QC solution.

File-based Content – QC Solution requirements

File-based content is processed through many stages from creation to archival. These stages are collectively called Content lifecycle stages. Content lifecycle stages commonly include Ingest, Edit, Transcode, Playout and Archival. At each stage, the content may be represented in certain formats and processed by a specialized infrastructure for a specific purpose. The subtle differences in formats support and the methods of processing at each stage can lead to unexpected problems in content. The QC solutions are expected to analyze such issues and ensure the content is verified to be ready at every stage of content lifecycle.

QC Across Content Lifecycle - At each stage of content lifecycle, the content needs to be verified (QC) for its internal details (formats, regulations, quality). Also at each stage, the type of content transformation is different - Editors change the content, Transcoders re-generate content and MAM solutions change header information. Hence there is a need for QC at every stage of content lifecycle for stage-specific verification. Also as the content size & volume grows, the efficiency of QC becomes an important requirement. Hence QC solutions have become a critical component throughout the file-based workflows as shown in the figure below:

For media companies that have multiple sites/business units, consistent QC methods across their business units’ help maximize their operational efficiencies. The growing global market of connected consumers also creates opportunities for media companies to consume content from any global supplier or supply content to any global consumer. The expanded content diversity and exchange further adds to the depth & breadth of QC requirements.

Anatomy of a good QC solution - A good QC solution needs to address multiple requirements in step with growing content and the diverse needs of media companies:

• Content-specific requirements – Does the QC solution offer a complete solution to verify a wide-range of content formats, delivery standards, regulatory compliance and quality at every stage of content lifecycle
• Efficiency & throughput requirements – Can the QC solution offer facilities to improve verification efficiency as the content size & volume increases?
• Enterprise-wide scalability requirements – Can the QC solution enable enterprise-wide groups achieve consistent and reliable QC methods?
• Global supply-chain requirements – Can the QC solution help expand content monetization in global markets as a trusted content certifier for suppliers and consumers

The following figure illustrates the four categories of requirements of a good QC solution:

QC Solution requirements – details

QC Solution requirement – 1: Content-specific requirements
A good QC solution should be able to support a wide-variety of content-specific requirements so the media companies can deal with any content at any stage of content lifecycle. The content-specific aspects include the following:

• Formats check – to make sure the content is in the formats it is supposed to be? The formats include the Container (MXF, LXF. Mov etc), Video essence (MPEG-2, H.264, J2K, DV etc) and Audio essence (AC-3, Dolby-E, WAV, MP3 etc). The QC solution should be able to handle format variations from various sources and still be able to check for format compliance to standard. An example of a standard format with many variations across infrastructure is MXF.
• Delivery check – The content needs to comply with delivery standards such as CableLabs VOD and ARIB depending on the region.
• Regulatory compliance check - In some regions of the world, content must be compliant with certain regulations. Notable regulations include loudness and flashiness control. Regulatory compliance checks are easy to support as they are well-defined in standards and are enforced only in some regions. For content targeted to broader global regions, regulatory compliance is not a major issue.
• Quality checks – As the content is transformed from each stage to another, its quality can be impacted. Common quality problems include freeze frames, black frames, blurriness, audio silence and many more. Some quality problems impact the viewer experience while others can lead to operational glitches (freeze frames). A good QC solution should be able to handle a multitude of quality problems and assess the problems correctly. Many QC solutions offer quality checks but few are able to offer correct assessment of the quality errors.

QC Solution requirement – 2: Efficiency & throughput requirements
File-based content is growing rapidly and QC of the growing content needs to be optimized with the customer’s existing computing resources. The QC solution should offer facilities so the verification can be made efficient. These facilities include partial verification (verify only problem areas), growing-file verification (verify as the file is being downloaded and reject download if there is a problem) and allocation of compute power to relevant QC purposes (large content vs high-volume content). Such efficiency and throughput facilities in a QC solution can help media companies scale their content QC seamlessly.

QC Solution requirement – 3: Enterprise-wide scalability requirements A common challenge across Enterprise-wide groups is consistency. When multiple groups across an Enterprise deploy their File-based QC solution, are they consistent in their content QC? Are they using same criteria to verify each content type? Any divergence in their approaches can lead to incompatibilities in content exchange within the enterprise itself and lead to inefficiencies. As the content QC grows into a large operation, there will be a need to ensure un-interrupted operation of QC farms. Such reliability is provided by capabilities such as high-availability. QC solutions need to support enterprise wide consistency and reliability as the customer requirements grow.

QC Solution requirement – 4: Global Supply-chain requirements
The ease of localizing file-based content offers the potential to quickly expand to global markets and maximize the content monetization potential. It is common to see same programs in multiple regions with local language sub-titling and editing to comply with local regulations. In a global market of multiple suppliers and consumers, there is a need for objective QC of content for better interoperability and quality. A good QC solution should be able to verify a globally diverse content but also the localization of content for each region. Such verification will lead to faster content exchange across more suppliers and consumers.

Summary

Media companies are actively moving to digital media and File-based workflows to leverage their content and reach connected-consumers world-wide. As the file-based content is exchanged across the growing content suppliers-consumers, it needs to be verified for quality. New generation of Quality Control (QC) solutions such as Interra’s Baton fulfill the need for content verification. The QC solution requirements start with comprehensive content checks for formats, delivery standards, regulations and quality. The requirements continue to grow with emerging standards, variations in content transformation for a wide-variety of suppliers-consumers world-wide. A good QC solution should address existing requirements and continue to support the ever-changing eco-system of formats and quality issues.

 

File-based Media Content – QC is Business Critical and Not an Option
- Krishna Uppuluri, VP Marketing, Interra Systems

Introduction

As the media transitions from tape-based to file-based digital content, the existing workflows and operational methods of media companies will need to be updated. This impacts Broadcasters, Post-production houses as well as Studios. Tape-based workflows relied on dedicated devices to transform the content at each stage of content lifecycle and physical storage such as tapes as a common means of content transfer. Such controlled eco-system of tape-based content was augmented by visual quality inspection of content at every stage. However, file-based workflows disrupt the legacy tape-based equilibrium drastically. A file-based content can be stored on traditional IT infrastructure, modified & analyzed by software and transferred via high-speed networks. This increased flexibility to transform and transfer content introduces new challenges in ensuring content quality across file-based workflows.

File-based Content – Growing pains and Need for QC

As discussed in previous section, file-based workflows enable much more flexibility to transform and transfer media content. The flexibility grows in tandem with the emergence of many digital media standards, the ease of editing, the ease of content localization for diverse regions and the diversity of targets for media content that include cable, satellite, internet and mobile platforms. The growing flexibility of content transformation and transfer offers more global opportunities for content monetization. The flexibility also increases the potential for content quality issues. The content quality issues can be automatically verified by the new generation of software solutions for file-based QC (quality control) such as Interra's Baton™.

Why is file-based QC important? With the emergence of high-definition broadcast and high-speed networks, global consumers will pay directly or indirectly to view the content anytime-anywhere on TV, Internet and Mobile phone. In such widely monetized content world, any quality issues in media content could have direct financial impact on media companies – either as operational inefficiencies or as opportunity limitations.

Operational inefficiencies - The following scenarios are a brief sample of content quality issues that impact operational efficiency:

• Content does not conform to a required standard
• Content freezes
• Content has extended blurriness
• Content does not comply with regional regulations (loudness or epilepsy control)

The resolution of content quality issues could require significant resources to resolve in terms of time and personnel directly impacting a media company’s operational efficiencies.

Opportunity limitations - If a media company wants to access content from external suppliers, it must be able to verify (QC) the content to ensure it meets the quality and regional regulatory requirements. Without the ability to verify or QC the external supplier content, the media company will be limited in leveraging the external content supply-chain. This could lead to delays and limitations in market expansion for the media company. Also, unverified content might not display properly on targeted platforms (Internet and Mobile), thus limiting the ability to monetize these new channels for content delivery.

File-based QC – Expanded scope

In the growing eco-system of file-based content, the traditional scope of Content Verification or QC has expanded to a broader scope. The single-point verification or QC has expanded to multi-point verification/QC spanning Ingest, editing, post-production, play-out and archive stages. At each stage, the Content verification ensures content quality and compatibility to the next stage of content lifecycle. The various aspects addressed by content verification or QC include:

• Formats – As the industry embraces various formats fine-tuned for various types of content and various target platforms, the content needs to be verified for 'formats conformance'.
• Quality checks – Content quality can be impacted either during transformation or during transfer. For example, content quality can get impacted during Transcoding, editing, file transfer and during tape-to-file transfer of legacy content.
• Regulatory checks – Content from one region may not be compliant with regulatory requirements in another region. Sample regulatory requirements include Epilepsy control, loudness control etc.
• Regulatory checks – Content from one region may not be compliant with regulatory requirements in another region. Sample regulatory requirements include Epilepsy control, loudness control etc.
• Content integration – The content may be required to be compliant to the server & software infrastructure in a media company in order to minimize content duplication, transfers and transformations.
• External content suppliers – The content formats can change based on the external content suppliers. In order to consider content from a supplier, a media company must be able to verify the content in its format. Without the ability to verify a given content, the media company cannot depend on contents from the respective supplier.

Interra's Baton

Baton is an Automated Content Verification or QC solution. Baton verifies file-based media content for formats conformance, Audio/Video quality, play-out specification compliance and more. As the file-based content evolves across various stages of workflow, the content is represented by various formats, metadata and requires relevant quality checks. In each workflow, Baton applies appropriate QC measures to check the format, quality & play-out specs compliance of the content.

Conclusion

File-based media content impacts the existing workflows and operational methods of media companies including Broadcasters, Post-production houses as well as Studios. File-based workflows offer opportunities to transform and transfer the content for broader monetization than ever. Content can be taken from creation to distribution faster, distributed to more regions and to more target platforms including traditional TV, IPTV and mobile TV. However, if the content has quality problems, it can have negative financial impact on media companies – either as operational inefficiencies or as opportunity limitations. Such problems can be minimized using the new generation of file-based QC software solutions. The QC solutions can ensure that a given content is ready for each stage of a content lifecycle and they can also expand the possibility of getting ready content from external suppliers.

 

Is Your Content Hazardous? Content Conformance to Legal and Regulatory Requirements

- Nitin Ahuja, Director Marketing & Biz. Development, Interra Systems

Media consumers have become increasingly discerning about the quality of content they consume its impact on the human senses. For example, Flashy video with rapid scene changes and sudden luma transitions is potentially harmful to people who are prone to Photo Sensitive Epilepsy (PSE). Rapid changes in Loudness levels – normally observed during commercial breaks in programmes – are another source of nuisance for consumers.

Governments around the world are realizing the need to regulate these aspects of media and are enacting laws to ensure that the interests of consumers are protected. Various organizations such as ITU, ISO, and ITC have formulated recommendations specifying concrete thresholds and restrictions on the temporal and spatial characteristics of media content. Once these laws go into effect, companies across the content supply-chain have to be aware of potential legal ramifications of non-compliance to regulatory laws.

This paper looks into some of these issues that may make the content hazardous for consumers and the resulting impact on the media industry. In particular, broadcasters need to increasingly ensure that the content that they broadcast conforms to various legal & regulatory requirements across various regions.

Introduction

Media industry has been associated with bringing entertainment to consumers. Content is an integral part of our lives across different screens – cinema, television, internet, & mobile. As media consumption increases, incidents have come to light where consumers have suffered physiological harm because of content issues such as Audio Loudness & Flashy Video.

Broadcasters around the world are facing new legal & regulatory requirements as governments/regulators are trying to control the harmful aspects of media content. Avoiding hazardous content is a matter of regulatory compliance on the part of broadcasters and can have financial implications if not addressed properly.

Audio Loudness

Background
Historically, the methods of measurement of phonic electric signal levels during sound production for radio and television broadcasting did not reflect the subjective reception of the sound volume by the public.

Complaints about loud commercials are a long standing issue. Advertisers had a self-serving incentive to be loud in order to get people’s attention. So, they developed material that was acceptable as per basic measurement techniques, despite being perceived as being loud by consumers.

A key challenge is to have a measurement technique that could consistently correlate with human perceptions when the program producer was creating the content. The attempts to encourage the development of a co-regulation mechanism did not work. Therefore, it became necessary to establish the new regulatory requirement for loudness.

Regulatory Landscape

ITU

• The International Telecommunication Union (ITU) recognized the loudness problem and its work gave rise to ITU-R BS.1770. The purpose of that standard was to establish an agreed algorithm for the measurement of loudness and the true peak levels of programmes. It is a robust standard which has the benefit of a simple implementation.

Poland

• On 15 December 2009 the National Broadcasting Council adopted an amendment to its Regulation of 3 June 2004 concerning principles of advertising and teleshopping in radio and television programme services.
• The amendment aims to limit the practice of excessively increasing the volume, as well as the violent, abrupt change of sound levels during radio and television advertising and teleshopping spots in comparison to the programmes preceding the advertising break.
• In order to ensure that this requirement will be properly exercised, the broadcaster is obliged to conduct comparisons of the loudness level of the programmes broadcast within the period of 20 seconds before the beginning of the transmission of advertising or teleshopping to the loudness level of each transmitted advertising and teleshopping spot.
• The technical rules of volume measurement level have been elaborated based on ITU recommendations: ITU-R BS.1770-Algorithms to measure audio programme loudness and truepeak audio level and ITU-R BS.1771-Requirements for loudness and true-peak indicating meters.

USA

• H.R.6209 - Commercial Advertisement Loudness Mitigation (CALM) Act requires the Federal Communications Commission to prescribe a standard to preclude commercials from being broadcast at louder volumes than the program material they accompany.
• The CALM Act refers directly to ATSC Recommended Practice A/85 "Techniques for Establishing and Maintaining Audio Loudness for Digital Television"

Europe

• The EBU has studied the needs of audio signal levels in production, distribution and transmission of broadcast programmes. It is of the opinion that an audio-levelling paradigm is needed based on loudness measurement. This is described in EBU Technical Recommendation R 128.
• In addition to the average loudness of a programme ('Programme Loudness') the EBU recommends that the descriptors 'Loudness Range' and 'Maximum True Peak Level' be used for the normalization of audio signals and to comply with the technical limits of the complete signal chain as well as the aesthetic needs of each programme/station depending on the genre(s) and the target audience.

Detecting Audio Loudness

The first research on the topic of how the ear hears different audio frequencies at different levels was conducted by Fletcher and Munson in 1933.

The curves as shown in Figure 1 depict how the human ear perceives loudness differently at different frequencies.

There has been a change in the leveling paradigm from peak normalization to loudness normalization. This is illustrated in Figure 2.

This change is vital because of a problem that has become a major source of irritation for television and radio audiences around the world – that of the jump in audio levels at the breaks within programmes, between programmes, and between channels. Loudness normalization is the solution to counteract this problem.

Broadcasters need to rely on automated content verification solutions to ensure that loudness is measured objectively rather than rely on subjective human verification.

Some important parameters while detecting audio loudness are:

• Acceptable duration of audio loudness
• Acceptable level of audio loudness
• Audio channel – cumulative or channel-wise
• Average loudness level
• Acceptable Duration of Audio Loudness

Different regulations have taken different approaches to loudness measurement. An “EBU Mode” loudness meter as defined in EBU Tech Doc 3341 offers three distinct time scales:

• Momentary Loudness (abbreviated "M") – time window: 400ms
• Short-term Loudness (abbreviated "S") – time window: 3s
• Integrated Loudness (abbreviated "I") – from "start" to "stop"

The CALM Act mandates adoption by FCC of the ATSC (A/85) that describes how to quantify audio loudness and then give a procedure for sending information to TV receivers to essentially adjust their volume control automatically to maintain a constant loudness. The technique used to quantify loudness is basically the same one used in the 1980s CBS system and is shown in Figure 3.

Flashy Video

Background
Photosensitive epilepsy (PSE) is a form of epilepsy in which seizures are triggered by visual stimuli that form patterns in time or space, such as flashing lights, bold, regular patterns, or regular moving patterns.

Persons with PSE experience epileptiform seizures upon exposure to certain visual stimuli. The visual trigger for a seizure is generally cyclic, forming a regular pattern in time or space. Flashing lights or rapidly changing or alternating images (as in clubs, around emergency vehicles, in action movies or television programs, etc.) are an example of patterns in time that can trigger seizures, and these are the most common triggers. Static spatial patterns such as stripes and squares may trigger seizures as well, even if they do not move. In some cases, the trigger must be both spatially and temporally cyclic, such as a certain moving pattern of bars.

The most common form of epilepsy, PSE afflicts as many as 0.8% of children aged 4 to 14. The number of diagnoses has risen in recent decades with the growing popularity of flashy video games, which can trigger a seizure. Most kids grow out of PSE by the time they're in their late teens. Although the condition has been recognized for years, no one has pinpointed what sorts of patterns are most dangerous or why.

• In March 1997, the 25th episode of an anime series called YAT Anshin! Uchu Ryoko had a similar incident when a reported four children were taken to hospitals by ambulances when a scene with red and white colors flashed.
• Photosensitive epilepsy was again brought to public attention in late 1997 when the Pokémon episode "Denno Senshi Porygon" (aka "Electric Soldier Porygon") was broadcast in Japan, showing a sequence of flickering images that triggered seizures simultaneously in hundreds of susceptible viewers (although mass hysteria caused 12,000 children to report seizure-like syndromes).
• 2012 London Olympics promotional film incident: An animated segment of a film promoting the 2012 London Olympics was blamed for triggering seizures in people with photosensitive epilepsy. The charity Epilepsy Action received telephone calls from people who had had seizures after watching the film on television and online. In response, it was reported that London 2012 Olympic Committee removed the offending segment from its website.

Regulatory Landscape

These incidents caused the UK and Japan to introduce Guidelines on the use and incidence of Flashing Images and Regular Patterns in order to protect photosensitive or potentially photosensitive viewers from provocative stimuli. The Guidelines seek to protect viewers by reducing risk of seizure from 1 in 4000 to 1 in 3 million.

Summary of UK Transmission Guidelines

• Luminance flashes or changes to and from saturated red may occur up to 3Hz. Higher flash rates are only allowed for up to 25% of the screen area.
• Stationary patterns containing more than 5 light dark bars should not occupy more than 40% of the screen area. Such patterns that oscillate, flash or reverse are restricted to 25% of screen area.
• Luminance flashes or patterns that violate the above conditions may still be allowed if the contrast between light and dark is less than 20 cd/m2 or if the darker component is lighter than 160 cd/m2 (maximum TV brightness is approx. 200 cd/m2.

Detecting Flashy Video

Detection of harmful flashes is normally done in accordance with Recommendation ITU-R BT. 1702. In accordance with this recommendation, there should not be more than 3 flashes in a second.

While checking for flashy video, the detection mechanism should check for:

• Rapid Scene Changes
• Luma Flashes
• Saturated Red Flashes
• Regular Patterns – examples could be light & dark stripes that are horizontal, vertical, slanted, or spiral that:
  • - cover more than 40% of a frame
  • - are stationary or moving (reversing, oscillating, changing direction)
  • - persist for more than 0.5 seconds
• If the pattern is moving slowly and smoothly, is should not be detected as harmful

Detection of flashy video in a media workflow is extremely difficult using traditional, manual verification or sampling techniques. A normal person who doesn’t suffer from PSE would not be able to detect flashiness in a video. Additionally, flashiness in a video affects different humans to different extent, thus there is a need for objective verification.

Automated content verification solutions help in ensuring flashiness compliance. Their faster performance makes it possible to verify the entire media content, not just a sample.

Summary

The media environment is changing as governments around the world bring in regulations to control potentially harmful aspects of media. Various organizations such as ITU, ISO, and ITC have formulated recommendations specifying concrete thresholds and restrictions on the temporal and spatial characteristics of media content.

Companies across the content supply-chain have to be aware of issues such as Audio Loudness & Flashy Video. There is enough regulatory guidance available for Broadcasters to establish mechanisms to control content issues that may make the content hazardous for consumers. The availability of Automated Content Verification Systems has made it easy to detect these issues in media content. It is a matter of regulatory compliance and not just a good-will act on the part of broadcasters.

References:

1. The Application of PSE guidelines to Electronic Screen Games, GFA Harding & MA Hodgetts
2. Loudness Metering: ‘EBU Mode’ metering to supplement loudness normalization in accordance with EBU R 128, [http://tech.ebu.ch/docs/tech/tech3341.pdf]
3. On the way to Loudness nirvana – audio levelling with EBU R 12, Florian Camere, [http://tech.ebu.ch/docs/techreview/trev_2010- Q3_loudness_Camerer.pdf]
4. SHADDAP image, [http://boingboing.net/2010/10/18/howto-make-a-proto-m.html]
5. Fletcher-Munson curve image, Wikipedia [http://en.wikipedia.org/wiki/Fletcher%E2%80%93Munson_curves]
6. The PSE Problem, [http://www.broadcastpapers.com/whitepapers/CambridgePSE.pdf?CFID=20622374& CFTOKEN=f80a13f481be2b68-9D4EDAFBC7FA- FE34-35B60531778306F1]
7. Congress Finds Time to Mandate Regulation of TV Commercial Loudness, [http://www.marcusspectrum.com/Blog/files/e8b16b656f420b948e3138a68342f521-161.html]
8. http://en.wikipedia.org/wiki/Photosensitive_epilepsy

 

Improve Workflow Efficiency with Automated QC throughout the Content Lifecycle
- Krishna Uppuluri, VP Marketing, Interra Systems

The migration of media content from tape-based analog to file-based digital media creates
opportunities to improve operational efficiencies across the content lifecycle. Factors contributing to operational efficiencies include human productivity, improvement in content throughput, quality, management and monetization across the content lifecycle. While the efficiency potential of file-based workflows is appealing, there are many hurdles to realize these efficiencies.

Tape-based workflows are driven by a rigid medium. The operational groups transform media content using dedicated devices, physically transfer the content and visually qualify the content hand off. New, emerging file-based workflows are driven by a more flexible medium, and they offer opportunities to speed up the content lifecycle. A file can be modified by software, analyzed by software and transferred via high-speed networks. From creation to playout, file-based content can be transformed and transferred faster. This increased flexibility and speed introduces new challenges to ensure the media content is correct at each phase of the content lifecycle. This need is fulfilled by recent technology advances in automated content verification/QC solutions.

Interra's Baton

Interra Systems' Baton is an automated content verification/QC solution that ensures content readiness of file-based media in terms of standards compliance, AV quality, playout specification compliance and more. As file-based content evolves across various workflows, the content is presented in various formats with its associated metadata, and it requires relevant quality checks at each stage. In each workflow, Baton applies appropriate QC measures to verify the format, quality and playout compliance of the content.

Automated content verification is a common thread across content workflows to verify every transformation and transfer of file-based content. Figure 1 illustrates how this QC solution can affect efficiency across workflows in the content lifecycle. Baton's content verification is objective and independent of any tools that transform the content.

Interra System's Baton enables automated content verification/QC in various workflows across all stages of the broadcast production chain

QC in Ingest, Post Production and Playout

The ingest process typically involves getting the content from multiple sources, such as traditional VTRs, tape libraries and live camera feeds, and from different locations. Externally, post-production teams or content providers can upload content to FTP locations; internally, interoffice files are transferred using smart automated file transfer utilities. The diversity of content sources, formats and locations make it difficult for content aggregators to ensure quality of the ingested content. A QC solution for this stage in the content lifecycle can speed content acquisition and enhance the supplier throughput to automatically comply with predefined specifications/quality standards. Baton can detect the artifacts at an early stage of the content lifecycle with simultaneous scans of multiple watch folders, FTP locations and shared SAN or NAS storage to optimize the ingest workflow.

The post-production process involves tasks such as content editing using nonlinear editing tools, closed-captioning insertion and stitching the contents into a timeline. The process also involves multiple levels of transcoding, including insertion of multilanguage audio and enforcement of regionspecific censorship policies. The post-production process is complex, and it can introduce many compatibility issues, quality issues in video, human errors or even insertion of incorrect audio or video that could remain undetected until playout. The QC solution in this workflow can ensure content quality, thus minimizing long delays and disruption to content monetization. Baton verifies transcoding defects and generates reports with embedded thumbnails, time code and content summary. Reports can be widely used as industry-standard, hand-off protocol between content aggregators and postproduction houses. Again, an independent QC is critical to verify that the transcoders have not negatively impacted the content quality.

The playout workflow typically involves compliance with playout specs and integration with automation infrastructure such as video servers and content distribution systems. The QC solution at this stage helps streamline the content workflow to avoid distribution errors. Baton supports various playout specifications and is integrated with video/SAN servers and file-transfer and content distribution systems to ensure content readiness.

Conclusion

File-based workflows can improve operational efficiencies across the content lifecycle. The digitized content in these workflows helps speed the content lifecycle, automate content transformation for enhanced monetization and enable operational cost savings. As content is transformed and transferred faster, automated content verification becomes a critical factor in streamlining and realizing the efficiency potential of file-based workflows.

 

Content Readiness - Ensuring Content Quality across Content Lifecycle
- Shailesh Kumar, Product Architect, Interra Systems

Abstract

With file based workflows, the content lifecycle has become much more complex and demanding. Content supply has also evolved introducing new models, such as user generated content. The technology evolution in these areas has led to a significant proliferation of digital media formats for supply and distribution. This has led to complex IT infrastructure and workflows for content life cycle management. Interestingly, as more content transformation is added to the workflow, more content quality issues arise.

Content quality issues directly impact the operational efficiencies in terms of human productivity, improvement in content throughput, quality, management, and monetization throughout the content lifecycle. In addition, the tight time-to-delivery limits content scrutiny and hence leads to more content quality issues. There is a critical need for automated QC as a multi-point process to ensure not only content quality but content readiness at all stages. Content readiness goes beyond the generally known quality issues to regulatory issues, workflow issues, and others. The resulting content readiness would have direct impact on operational efficiencies across the entire content lifecycle.

Introduction

Content lifecycle involves multiple stages of workflows, multiple content transformations, and content transmissions. The content transformations include formats, characteristics, meta data, layout, and more. At each transformation, content interacts with diverse systems and technologies. To increase audience reach, the content needs to be delivered to multiple target platforms (broadcast, cable, IPTV, VOD, mobile, web) across multiple demographics (with varying regulatory standards) and for a wide variety of devices.

Throughout this fast moving content life cycle, content transformations, transmissions, and interactions impact content quality. Content quality is a multi-point process rather than a single-point event just before content delivery. A continuous QC process ensures content readiness which impacts operational efficiencies across a file-based workflow.

Content Readiness

Content readiness is a measure of the relevance and conformity of content at each stage in the content lifecycle. Content readiness spans a few attributes:

• Standards/formats conformance
• Quality issues specific to a stage, such as ingest or post production
• Regulatory conformance
• Content specifications
• Infrastructure fit (content access, alerts, reports)

Traditionally QC focused on formats conformance, and native content quality checks, but content readiness goes beyond the traditional QC. Content readiness deals with continuously expanding content checks to meet with regulatory issues (loudness, flashiness) and user experience issues (video signal levels). Content readiness also ensures that content suppliers meet specification issues of the content consumers (playout) and workflow issues. Workflow issues include, content access from where it is, when it is ready, verified for expanded quality, and stored appropriately

Content Quality Requirements across

Content Lifecycle As emphasised earlier, content quality is impacted across a workflow. Figure 1 illustrates a content flow and a sample of typical quality issues that are possible at a particular stage.

Ingest - The ingest process is responsible for ingesting audiovisual signals into the content rich organization. The signal may be an incoming feed from satellite or cable, or a signal from a studio device, such as a tape, a DAT, or a CD recorder/player. The signal is digitized during ingest and may be stored in multiple formats via suitable encoders and written to an online storage system. There may be pre-existing problems in the incoming audiovisual signals. Moreover, the encoding process at ingest may introduce some more errors. In addition, content may need to meet facility specific requirements.

Editing - Editing with Non-Linear Editing (NLE) systems typically involves exporting the data from Content Management Systems (CMS) to NLE system for editing and importing it back after editing is complete. These two operations may introduce several kinds of errors. If reencoding of data is involved, it may cause loss of quality. Changes in wrapper formats may also introduce some standards conformance issues. Apart from import and export, the editing activities (cutting, trimming, multiplexing, de-multiplexing, color correction, special effects filters) may introduce unwanted perceptual errors in the content.

Archival - Tapes are used as near-online storage for archiving content that is not in active use. Tapes are heavily used for high bandwidth, high resolution studio content since storing them in hard disk based online storage is usually very costly. If content resides on tapes for long time, it may degrade slowly. Periodic checking of content ensures its integrity for long time.

Playout - Before final playout, content is transcoded for the target delivery platform. At this stage, content quality needs to meet customer expectation. Transcoding typically converts audiovisual signals from HD to SD or lower resolutions as per the needs of target platform. Compression with B frames is used to reduce final content size. Such operations are expected to reduce the perceptual quality of content. Hence, it is imperative to measure the perceptual quality at this stage to make sure that it doesn’t fall beyond the levels expected by customers.

The fact of the matter is that errors may be introduced at any stage throughout the content life cycle and detecting an error early in the workflow can save a lot of time later. If QC is not performed at an early stage, it may be quite difficult at later stages to identify the source of the issues in content. Figure 2 illustrates how efficiency is affected when an issue in content propagates and is discovered too late in the flow. In this illustration, ingested content has some I frames with block error. Block error may have been introduced during digitization. This issue is not detected at ingest. When content is finally transcoded to MPEG-2 video, the block error in I frames is propagated to the B and P frames. The content, of course, is not ready for playout. The error trace leads to the ingest stage affecting efficiency and delivery.

Quality Issues in Digital Content

Quality issues can be broadly classified into: regulatory issues, user experience issues, high-level facility/workflow requirements, standards conformance issues, and encoding errors.

Regulatory Issues
Regulatory standards are newly emerging requirements in content specification and mandatory in some countries, such as Japan and UK. Regulatory issues cannot be easily detected or measured through manual QC.

For example, rapid scene changes and sudden transitions in luma and red color, or regular patterns are potentially harmful to people who are prone to Photo Sensitive Epilepsy (PSE). Manual QC cannot detect flashy video until a person is affected by PSE. Again, the level of disturbance caused by flashy video may vary from person to person. There are ITU recommendations, which describe specific objective measurements for detecting harmful flashes. ITU-R BT. 1702 specifies how harmful flashes can be detected and how a video can labeled as flashy. Similarly, high pitches in ad inserts can irritate viewers. So ITU-R BS.1770 specifies audio loudness limits and a measure to check audio loudness.

User Experience Issues
There are several user experience issues, which may or may not be detected with manual, visual QC. Blockiness may be present due to low bit rate coding. Blockiness may also be present due to the encoding equipment’s rate distortion algorithms. Processing of video content through different filters may add blurriness. Combing artifact may be present in high motion interlaced sequences. Transcoders may transform encoding errors into perceptual errors. For example, missing or misplaced slices (encoding errors) after transcoding may be converted to perfectly valid bit streams containing stripe errors. Freeze frames may occur due to video capturing issues, or when encoders may drop some frames to meet bit rate objectives. Field dominance may be present at places where video sequences with different field orders are stitched together.

Some user experience issues cannot be detected with manual or visual QC. These include issues such as color gamut issues or video signal level issues. However, these issues affect the user experience.

It is possible to check these artifacts programmatically. Let us look at video first. The general strategy works as follows. The video essence is fully decoded into baseband (uncompressed) and pixel values are examined for presence of visual artifacts. Blockiness can be measured by looking at pixel value differences at block boundaries. All the frames in a sequence can be characterized by their blockiness index and segments can be easily identified where the blockiness level is beyond a user-defined threshold. Color gamut is measured by counting the number of pixels whose values go beyond the permissible limits in the specified gamut. Users can specify maximum acceptable percentage of out of gamut pixels. Pixelation is detected if the amount of detail in specific parts of a frame is missing. Similarly for audio, audio samples can be averaged out to measure level and loudness. Left and right channel samples can be compared to measure level and phase mismatch. Spectral analysis of audio samples can help in identifying the presence of specific kinds of noises like transient noise. Similar techniques exist for objective measurement and detection of a wide variety of audio and video perceptual defects.

Meta Data (Workflow) Requirements
There are specific requirements for ingest or delivery at a particular facility. This can vary from one facility to different facility and also depend upon the kind of facility (e.g. post houses vs. broadcasters). A post house may be required to submit content to its customers with specific requirements. E.g. the audio content may be required to be in a specific format (PCM, FLAC), at a specific resolution (16-bits per sample), at a specific sample rate (44.1 KHz). Video content may be required to have characteristics, such as MPEG-2 main profile, 4:2:0 chroma sampling, ITU-T BT-601 color space, minimum bit rate 15Mbps, Long GOP, 640 fixed horizontal dimension, 1:1 pixel aspect ratio, 29.97 FPS. Such requirements are defined by broadcasters or content distribution networks and post houses are required to comply with it. Manual checking of these parameters is tedious, while an automated QC solution can parse the digital media data, look at the corresponding parameters in the file and verify them against the specifications quickly and easily. Similarly, when broadcasters release their content over cable networks, they must make sure that their content meets the requirements of the set top boxes on which the content is required to be played.

A related problem is ensuring correctness of meta data associated with content. There are two kinds of meta data. Structural meta data is for machine consumption. It includes information such as encoding used to compress video, audio, aspect ratio, resolution, presence of AFD, teletext. Descriptive meta data is for humans to read, e.g. Title, cameraman, producer. Meta data may be stored separately in XML files or databases or it may be embedded inside the content (as in MXF files). An automated QC solution can easily verify correctness of structural meta data. It can identify any discrepancies in meta data and report it. A QC solution integrated with CMS may also update structural meta data with corrected values. Descriptive meta data is usually examined and corrected manually.

Let us look at an example where a video with jitter motion is played out due to meta data error. A DV interlaced file (SD DV is bottom field first) is ingested to a workflow. The trascoded playout required is MPEG-2 in top field first display order. The captured DV video is bottom field first. The transcoder receives incorrect meta data in the picture header, which specifies Top Field First. The final display order is affected leading to video jitter as depicted in Figure 3. A QC solution could have analyzed the sequence of frames and determined whether the original content was top field first or bottom field first or progressive (by looking at the pixel values). The QC solution could then check the correctness of field order meta data associated with the content against the actual field order information inferred from content. An application/system could then be triggered to correct the field order meta data or reject the whole content.

Let us look at another example where incorrect AFD (Active Format Description) meta data can result in faulty upconverted video. AFD meta data is required at upconversion or down conversion. Typical SD to HD conversion or display of SD content on HD monitors may happen in one of following ways:

• Full resolution content is mapped to HD by adding pillar boxes
• 16x9 anamorphic content is mapped to HD by expanding the content back to 16x9 space
• 16x9 letter box content is mapped to HD by removing the top and bottom bars and dislaying the content only

2 and 3 are possible only if the conversion / display process is AFD aware and AFD flags are present indicating the fact that SD content is either 16x9 anamorphic or 16x9 letter box. This is done when AFD information describing how the SD content is laid out is present and the conversion/display process is AFD aware.

If AFD information is missing or incorrect, the following could happen:

• 16x9 anamorphic content is made worse by adding piller boxes around it
• 16x9 letter box content becomes a postage stamp content by adding further pillar boxes to it as depicted in Figure 4

To handle AFD issues, a QC solution can be used to determine the presence of black bars. If AFD information is not present, the QC report can be used to identify the right AFD and assign it with content. If AFD information is present, the QC solution can be used to verify its correctness and in case of error, AFD information can then be corrected.

Encoding Errors
Encoding errors are introduced by problems in the audio/video encoding or transcoding equipment. They may also be introduced by transmission channel if some media data gets lost or corrupted during transfer. Consider the picture below.

In the picture, we can see that data for a specific macroblock in the picture seems to have been copied in the top left and the macroblock in the middle seems to have been blackened. Detailed analysis of this video sequence reveals that a horizontal motion vector component was found to be out of picture boundary in the encoded video data, which resulted in this error.

Here is another picture.

In the above picture, macroblock vlc code could not be decoded for the first macroblock in the first slice of the picture. Thus, the whole slice is corrupt. Interestingly several decoders have error concealment techniques builtin, and they may hide such errors during playback. Whereas an automated QC solution will go through all the bits of media content and diligently find all kinds of encoding errors and report them. A QC solution doesn’t require any error concealment strategy. Rather, we expect it to be designed with error revealing strategies.

Standard Conformance Issues
Digitally encoded media data contains lot of structures (video sequences, access units, pictures, slices, macroblocks, blocks, sequence headers, picture headers, macroblock headers, PES packets, transport packets) Different standards define how these structures are to be organized and interpreted in a media bit stream and what are the semantically valid values in these headers. Incorrect values may lead to problems in decoding and using the media data later. Here are some examples: The profile or level fields in an H.264 sequence parameter set may be invalid. Reference picture parameter sets or sequence parameter sets may be missing. The address of a coded macroblock may be beyond the allowed range in a picture. The cropping parameters may be incorrect. Adaptation fields inside transport packets may be incorrectly encoded. Continuity counter in transport packets may not be properly maintained. Apart from this, there may be several constraints on the size of data. E.g. an H.264 NAL unit may be too large for a given H.264 profile and level. The video data may not be conformant with coded picture buffer conformance model leading to situations where it may not play well on memory constrained devices. These errors cannot be detected by manual inspection and require sophisticated QC tools which have complete support for standards compliance.

Broad Requirements of an Automated QC Solution

As stated before, content verification or QC is a multipoint process to ensure content readiness throughout the content lifecycle. This means a QC solution must be able to handle all aspects of quality checking specific to every stage across the content lifecycle. This includes planning, formats, checks, workflow integration, and much more.

QC Planning Process
Different stages in content life cycle require different kinds of content checks. The QC solution should take this into account and provide flexible mechanisms for setting up different kinds of test specifications at different stages or for different types of content.

The solution should provide ways to select the essence and container formats for which the tests are being performed. The solution should also provide ways to select specific perceived video/audio quality checks as deemed required at different stages in the content life cycle. In addition, the solution should provide ways to specify facility specific requirements at different stages in workflow. It should also be possible to exchange these specifications between different deployments of such a QC solution so that multiple workgroups possibly spread across multiple sites or organizations can benefit from well-developed test specifications.

Workflow Integration
QC solutions should provide easy hook for integration into a workflow. The QC solution maybe loosely coupled with workflows or maybe tightly integrated with MAM systems or workflow engines. A tight integration requires API support for programmatically controlling Baton inputs, job and outputs handling The QC solution should provide effective notification support in form of email alerts and/or TCP/UDP based alerts.

Extensive Format Support
The number of digital media formats (essence containers, exchange formats, essence formats) has increased significantly. Some formats are wide spread while some formats are applicable to niche domains. The QC solution is expected to provide support for all these formats.

Extensive Checks Support
Different stages in the workflow introduce specific errors. A comprehensive QC solution is expected to provide support for workflow specific issues. In addition, the solution should provide support for regulatory issues.

Universal Content Access
There are a wide variety of content servers in use in different facilities. A particular facility grows its infrastructure over time and this naturally leads to different kinds of content servers existing within the same facility. The QC solution is expected to provide support for all these content servers to access content. These include different flavors of FTP servers, dedicated video servers like Omneon, SeaChange etc., UNC based access from servers like Avid Unity ISIS, to name a few.

Scalability and Availability
As content organizations grow, the amount of content to be verified keeps increasing. The QC system should be scalable with the hardware resources so that more verification capacity can be achieved easily. In addition, the QC solution should be available as a service, which is accessible to any agent (human or machine) 24x7. Redundancy should be built so as to ensure that in case of software or hardware failures, the QC operations are not interrupted.

Throughput and Performance
It is crucial for the verification of individual files to be completed as fast as possible. The performance depends upon several criteria. Higher resolution and higher bit rate content usually takes more time to verify. More perceptual quality checks take more time. Some formats (like H.264) are more complex (c.f. DV), so they take more time to verify. While it is usually possible to verify SD content on a single core, HD requires much more effort. QC system should be designed to take advantage of recent multi-core machines by parallelizing verification work on available cores. Moreover, the system should be designed to verify multiple files in parallel by adding more hardware to the system. Guiding the users to define the right level of testing for a given content can also help speed up content verification or QC. Some QC solutions already offer such guidance in their environment.

Meta Data Extraction
The QC solution should provide for ways to extract structural meta data from content as part of its content analysis report. It should fully examine meta data information available at the wrapper and essence levels and report any discrepancies found between the two. If meta data is placed in other sources (like associated XML files), the QC solution should provide ways to include them in content verification process. It should be possible to use this information to update meta data in the CMS or embed the information in the content with correct values.

Independent and Objective QC
The QC solutions should be able to verify content independent of workflows or tools that transform the content. They should provide objective reports of the content quality that are again independent of any biases to a specific workflow or a tool.

Challenges in Automated QC

The challenge for automated QC solution lies in ensuring the continuity of the solution. There is a constant evolution of content formats and technologies used in the workflow. The QC solution needs to constantly upgrade itself meet the quality requirements of new formats. More so, the QC solutions constantly need to be in sync with the quality issues introduced by new technologies or methods of content production/editing. With the splurge of content generation techniques and several regulatory standards being evolved, the QC solutions needs to constantly be on an evolutionary path.

If automated QC is expected to be integrated as a continuous process in a workflow, the solution needs to integration ready for various kinds of workflows and technologies used in the workflow.

Error reporting is a major challenge. The QC solution is expected to accurately report all errors and warnings found inside a media file during verification. Not all computer algorithms can be deterministic in detecting quality issues on real world audio-visual content. There are two kinds of issues, which may arise with the results generated by the QC system: false positives and false negatives. A false positive happens when an error is reported which doesn’t really exist. E.g. blurriness may have been introduced on purpose in some shots, which gets detected as an error by a QC solution. An operator on looking at error details may choose to ignore such an error. A false negative happens when an error, which exists in the content, doesn’t get reported. This is not acceptable since the error passes through the automated workflow and nobody gets to know about it. Error detection algorithms in the QC system should be designed with a conservative approach. They should avoid false negatives while a limited number of false positives should be manageable once in a while.

Conclusion

Automated QC is a continuous process to ensure content readiness across file-based workflows. Content readiness impacts operation efficiencies. Not all content quality issues can be detected by manual, visual QC. Hence, there is a need for an automated QC. A comprehensive QC solution should support extensive formats, quality checks, objective and independent verification, enterprise scalability, high availability Continuity of automated QC also requires accurate results, integration with other technologies, and evolution in step with the industry trends. Automated QC is a mainstream requirement today and companies involved in content supply-chain are adopting the QC solutions as a means to improve their content quality as well as to improve their operational efficiencies.

References

1. Professional content management systems, Handling digital media assets; Andreas Mauthe, Peter Thomas; John Wiley & Sons, Ltd; 2004
2. ISO/IEC 13818-1 and ISO/IEC 13818-1:2000/Final Draft Amendment 3ISO/IEC 13818-1(MPEG-2 Systems)
3. ISO/IEC 14496-10, Advanced video coding for generic audiovisual services
4. ISO/IEC 13818-7:2006 Information technology -- Generic coding of moving pictures and associated audio information -- Part 7: Advanced Audio Coding (AAC)
5. WAVE PCM sound file format
6. BT.1702 : Guidance for the reduction of photosensitive epileptic seizures caused by television, ITU-T, 2005
7. Baton 3.0 user manual (www.interrasystems.com)

Baton Case Study - EuroTek - OBU (Irish Parliament)

Background

The requests to make rich media content available anytime, anyplace and in any format continues to push organizations worldwide to implement automation into their digital media workflows. As digital media content grows, there is a growing need for proper archival and the ability to access past content without deterioration of quality.

Eurotek Ireland Ltd., a Dublin-based systems integration company, was contracted by the Oireachtas Broadcasting Unit (OBU) to provide a digital acquisition and archiving system for the Houses of the Oireachtas (Irish Parliament) to replace the existing Sony Newsbase system.

Working closely with OBU and with Windmill Lane Ltd’s Leinster House Television division (LHTV), who are responsible for technology and operations of the Broadcasting Unit, Eurotek were able to ensure the tight deadlines were met and install the new system with minimum disruption to the unit’s operations.

As a key imperative to providing access to content, OBU required automated content verification of all incoming & outgoing content, while avoiding high resource requirements given the large content volume.

Solution Architecture

The system is based around IBIS iFind tools, with Omneon Spectrum servers, Omneon MediaGrid Active Storage System, and integrated Interra Baton automated QC software. This includes Telestream Pipeline network encoders to provide a redundant recording path into the Omneon MediaGrid. Two Avid Media Composer editing systems, with MOJO-DX hardware, are provided for craft editing, with Marquis Broadcast’s Medway providing media transfer between the servers and editing suites. The recorded media is archived to a Sony PetaSite with LTO-4 tape drives, providing in excess of 10,000 hours of media storage at 50Mbit/s MXF wrapped media. SGL Flashnet archive management software provides comprehensive rules-based archive management, and is integrated into the IBIS iFind software suite, providing the operational staff with a very easy to use interface to archived media. Key to this project is access to growing files transferred to the Omneon MediaGrid and managed by IBIS iFind in order to allow operational staff to mark points of interest, add metadata and produce highlights with the incoming media.

The system is designed to supply up to 12 channels of simultaneous ingest/playback via the Omneon Spectrum server, providing primary recording of the output of the OBU’s two main chamber production galleries, and four committee room galleries, with additional channels for playback, lines recording, and other requirements.

"As described above, the solution required diverse software and hardware infrastructure. Baton for QC helped us achieve two major objectives – Minimum content duplication and maximum value out of the full solution for content readiness. Baton’s extensive solution scope and integration readiness with the rest of infrastructure helped us achieve our objectives easily", said Kevin Moore, Director, Eurotek Ireland.

The fast pace of digital content today demands that verification systems must operate on a 24x7 basis and ensure content readiness across all stages of the content lifecycle.

Baton is used by a range of global media companies to ensure content readiness throughout their content lifecycle - from Content creation to content aggregation to Content distribution. Baton is well differentiated from competitive solutions based on its built-in support for extensive formats, most complete quality checks, enterprise scalability and ease of use. Using Baton, customers can achieve a 24X7, automated, objective method to ensure content readiness.

The Omneon MediaGrid active storage system combines clustered storage with grid computing, using multiple interconnected-yet-independent nodes to create a scalable system that can serve as a grid-processing engine for processor-intensive media processing applications.

Baton uses the Omneon MediaGrid Processing Framework to harness the processing power of dozens of CPUs within MediaGrid to verify content. Baton’s core is the Verification Manager engine, which runs on a Windows server and connects over Ethernet to the MediaGrid active storage system. To speed the process, Baton verification tasks are executed in parallel on the many CPUs in the MediaGrid.

Baton Content Readiness goes well beyond the traditional QC with built-in support for most formats including SD and HD, audio/video checks, metadata extraction & pre-defined play-out.

Solution Benefits

1. Achieves content readiness with minimal investment in additional verification hardware or digital island storage.
2. Content Verification in-place reduces load on network infrastructure, with no need for additional client network bandwidth.
3. Significant increase in performance over standalone QC appliances, streamlined maintenance of the overall system.
4. Simplification of workflow by minimizing file transfers between the storage system and any external processing systems.
5. Comprehensive formats support – Container, Video & Audio
6. Most complete quality checks – including blockiness, blurriness, flashiness, loudness, Field-order detection.
7. Enterprise Scalability - including software maturity, Automatic Testplan generation, Partial verification, Verification scalability across servers/cores, High-availability etc.

 

Joint White paper by Interra & Signiant

Background

As media content shifts from a tape-based to a file-based workflow, the status quo of content lifecycle becomes disrupted. The disruption spans two dimensions - faster lifecycle and new transformation activities. The lifecycle from creation to delivery would be significantly faster for file-based workflows compared to tape-based workflows due to the dynamic nature of the content. Content is also impacted by many new transformation activities. For example, material now arrives from new sources such as from user generated content and can be modified by new players (further blurring the lines between production and broadcast facilities). Content also must be modified in new ways due to multiple target platforms, demographics and devices, such as wireless, regional localization and handhelds.

In traditional tape-based workflows, the concept of quality control (or QC) had a specific point of applicability and in the context of a specific activity (such as post-transcoding). With file-based workflows, the concept of quality expands to content readiness. Content readiness spans multiple points of applicability in multiple contexts of activities across the content lifecycle. The disruption in content lifecycle due to file-based workflows now expands beyond faster lifecycle and new transformation activities to a third dimension—that of content readiness.

This third dimension of content readiness spans the entire content lifecycle and needs to be addressed with a consistent solution. Without this, file-based workflows become vulnerable to inconsistent user experiences for content consumers and will result in limiting the monetization of content for content owners.

Content Readiness - The Third Dimension

The third dimension of content readiness is an objective assessment of content and directly impacts consumer experience and supplier monetization. In this context, content readiness goes beyond traditional QC. Here are some of the requirements to ensure content readiness in file-based workflows:

• Must operate on a 24x7 basis – because content files move automatically and faster across the network than the physical distribution and manual manipulation of videotape
• Must support all content attributes - at all stages of content lifecycle with comprehensive support for all popular formats and common audio/video checks
• Requires built-in validation for each stage, such as metadata extraction, pre-defined playout specifications, etc.
• Must fit into automation initiatives- support multiple workflows and automation environments across the content lifecycle

Content Readiness - Points of Action

Content readiness spans the entire content lifecycle. What are some of the possible points of action for content readiness? What stages of the content lifecycle does content readiness specifically apply and how does it fit into the respective automation components? This can be a subjective discussion depending on the content lifecycle flow, the participants, the automation infrastructure and the sequencing of events (e.g. who performs which activity, what is the person-to-person hand-off, what is the process-to-process order?). The following diagram assumes a centrist approach for a typical file-based workflow content lifecycle and highlights relevant points of action for content readiness.

Content Readiness - Solution

Interra’s Baton is an automated content verification system to ensure content readiness throughout the content lifecycle. Baton is a software only solution that is differentiated by the following aspects:

• Most comprehensive support for content formats
• Most comprehensive audio/video quality checks
• Supports fast validation based on metadata extraction and pre-defined playout specs
• Readily integrated into many standard workflows and automation environments at all points of action

Signiant’s content distribution management software accelerates, secures, automates, and centrally manages the distribution of digital media.

• Central Dashboard providing full visibility into all global transfers
• File transport acceleration and latency compensation with 95+% bandwidth optimization
• Full Certificate Authority for security, media encryption, and certified delivery
• Drag and Drop Workflow Modeling Engine for creation of automated workflows

Content Readiness– Sample point of Action with Baton-Signiant Integration

The integration of Baton and Signiant’s Workflow Modeling Engine enables end-to-end visibility into the content readiness lifecycle. Through a drag-and-drop user interface, users can create unlimited numbers of workflows that support content ingest, transformation, quality control, distribution, and confirmed delivery. By collaborating on an API-level integration Baton will process files delivered to it via Signiant, run the required content verification routines, and based on pass/fail conditions, Signiant will then deliver the files to required destinations. The result of this collaboration is a streamlined, automated content verification and content readiness solution that can operate on a 24x7 basis in a “lights-out” operation. As a result, content can more easily flow from its origin point, through transformative and verification processes, and to distribution/consumption points.

Conclusion

This white paper discussed the disruptions in content lifecycle as media content shifts from tape-based to file-based workflows. Beyond faster lifecycle and new transformation activities, the third dimension of content readiness has been highlighted. Content readiness has multiple points of applicability across multiple contexts of activities across the content lifecycle. The automated movement and content verification is defined in some detail with sample solutions using Interra’s Baton integration with Signiant’s distribution workflow. While the specifics details of content readiness may vary across the customer spectrum, the need for a consistent solution for content readiness remains critical. Otherwise, file-based workflows will be vulnerable to inconsistent user experiences for both the content owner and the content consumer.

 

Video Quality Issues in File-Based Broadcasting
- Shekhar Madnani, Product Architect, Interra Systems

Abstract

The media industry is rapidly migrating from tape-based media acquisition and broadcast to file-based workflows. This migration has resulted in many different dimensions of impact on the media content. The transformation of media content occurs at several stages in the flow. The transformation could start from conversion of analog to digital media and be affected by various systems involved in processing and delivery of media. The digitization of content has led to several changes in compression standards, editing, and transmission technologies. There are various options to create, edit, and repurpose the content. Additionally, the industry has to deal with evolving media compression technologies, container and delivery formats. There are several transmission methods based on delivery needs, such as IPTV, DTH, cable, and VOD. All these dimensions of impact on media content have increased complexities in a file-based broadcast workflow. Hence, there is increasing uncertainty in the quality of content that reaches the consumer. The consumer expectation of HD video and the increasing competition in media industry further add to the quality requirements of media content. Therefore, file-based broadcasting has to deal with constantly evolving technical complexities on one hand and expectations of quality by the consumers on the other. In this scenario, the legacy methods of quality control are inadequate. Manual checks become inconsistent, subjective, and difficult to scale in a globally accessible media workflow. This paper discusses the types and causes of issues that affect the quality of media in various stages during broadcast workflow. The paper looks at the adoption of automated tools for accurate detection of issues in media content to improve the content quality & consumer experience.

Introduction

The adoption of file-based media has spearheaded many advantages for broadcasters. There is ease of media storage and retrieval. There is the enhanced flexibility, speed, and sophistication of non-linear editing. File-based content has even changed the way media is delivered.

In the tape-based flows, many of the processes were handled manually and were cumbersome. With the newfound flexibility of file-based flows, the media files are being compressed and formatted using a wide range of compression technologies, file format types, and delivery formats. With the flexibility of digital data, complex operations are possible to create various types of output files using sophisticated editing techniques, repurposing, and transcoding.

The increase in complex operations on media files increases the possibility of injecting errors into the content. These errors can manifest in metadata of file formats. There may be errors with respect to the non-conformance to variety of compression standards. There may be errors related to degradation of video and audio quality. There may also be errors introduced during digitization of tape-based media.

In addition, the advancement of HDTV has led to the end consumer being media quality aware and more concerned in terms of the value for their money. Broadcasters have now added additional systems to check the end user media quality. These checks are performed either manually or automatically.

Thus, complexities in a file-based broadcast flow have been impacted by:

• Transformation of media content that occurs at several stages in the flow.
• Standards and technologies in media industry that have influenced compression standards, editing, and transmission technologies.
• Transmission methods based on delivery needs, such as IPTV, DTH, cable, and VOD.
• Consumer expectation for media quality propagated by technologies, such as HDTV.

This paper discusses existing scenario of file-based media broadcasting, the causes and effects of media quality degradation at various stages of a file-based workflow, and the advantages of automated quality verification of content.

File Based Workflow: Existing Scenario

In the pre-digital content flows, the traditional broadcasting environment dealt with media that was in tapes and handled manually by individuals. The media was captured at the studios, stored, sent for post-production, and then ingested. The ingested media was labeled with some known metadata for later retrieval through mechanical or automated systems.

With digital content, file-based workflows have started evolving rapidly. A generic file-based scenario is depicted in Figure 1.

The first stage is media capture, which can be a capture from camera within a typical studio or production house. This is the production stage of the media in which the video can be stored in formats such as DV, MJPEG, XDCAM, etc. The capture can also be achieved using network resources, such as FTP. The capture can also happen after conversion of media available from legacy tapes.

Ingest is a process of transferring or accepting content to or within a digital editing / storage system. This process includes operations such as digitizing the content from analog tape, inserting metadata for efficient retrieval from a very large database of files. The ingest process includes embedding the metadata within known formats such as MXF and MOV.

In the post-production stages, the media is processed and edited. Here the processing includes adjusting color values for increasing/decreasing the brightness and removing some frames from the captured video. This stage usually does not involve any loss of quality after real capture.

Before the distribution of media content, the media has to be processed again to satisfy the requirements of the distribution network or ultimately the end consumer. This processing can be in the form of transcoding in which the bit rate of the given audio/video is altered. The processing could also involve change of compression format of the given audio or video.

The automation system involved would then schedule the transcoded media to be distributed to end consumer systems or networks involved for delivery.

Each stage in the workflow has different types of files based on its contained media, the file format used, the bit rate, frame size, and frame rate. The files are created at various stages and stored in the storage systems with the applied metadata scheme. For efficient access and search, there are automation systems at various stages of the content flow.

Video Quality Issues

The above file-based workflow spanning capture, post-production, and transcoding, involves numerous cases of media transformations. The numbers of cases of transformations depend on the requirements of a given broadcaster or a vendor. These requirements in turn affect the complexities involved, which in turn increase the possibilities of errors in content.

A broadcaster has to validate media received from a vendor or production house. The objective is to check for any degraded content prior to it being ingested into the workflow.

At ingest, there could be video quality issues, such as blurring, brightness, or flashing. For example, in case of flashing, the video should not contain the temporal and spatial patterns that would induce seizures in photosensitive-epileptic viewers. If flashing is not checked at the time of ingest and delivered to the customers, it could lead to severe legal implications for the broadcasters.

In case of tape-to-file conversion systems, there could be issues related to some part of the video not being captured or part of captured block getting noisy due to dirt between tape heads and tape.

After ingest and editing or repurposing, there could be a variety of video errors because of erroneous handling of video streams by editing systems or editing experts. The editing may involve cutting and pasting of content into/from the video stream. This operation may disturb some of the already known and fixed parameters such as field order, required telecine, and field-dominance. If a new video were inserted in an existing content, there would be an issue of field dominance near the location of join. The editing may also involve inserting color bars or black frames for specified time duration within the stream. The durations of these types of sequences needs to be rechecked before the next stage. The requirement of putting special effects or adding graphics may disturb existing sequence signal levels.

The transcoding stage refers to transforming a given media from one format to the other. The transformation can be with respect to the container format such as MP4, DV, MXF, and MPEG2 TS, or it can be resizing the video frame size, changing the bit rate or sampling format. The conversion may also involve changing the compression format from MPEG2 to H264, DV to MPEG2 at some specified bit rate and other parameters. For example, there could be a requirement of changing the container format from MPEG2 Transport stream to 3GPP format for 3G mobile distribution networks. After the transcoding, issues such as blockiness, pixelation, combing, blurring, or ringing can reappear in content.

Consider a case of blockiness artifact as a well-known issue of video quality. This is the most common artifact in case of transform based video compression schemes. The artifact starts appearing while transcoding in lower output bit rate for a highly detailed video. In a general case of MPEG compression scheme, an input frame is divided into smaller independent entities called as blocks. Each of the blocks is transformed to frequency domain using transformation such as DCT (Discrete Cosine Transform). The transform generates discrete frequency coefficients where the low frequency coefficients would have more weightage for representing information within a block. If a block contains high details, coefficients for high frequencies may also contain important information. Lowering the bit rate would result in lesser bits being allocated for each of the blocks. In this case, the blocks would be forced to ignore coefficients at higher frequencies and lesser bits would be included in output encoded video stream. At the decoder side, the inverse transform would generate a block. If the block contains very few edges or is visibly smooth, then ignorance of higher frequency components would not effect the reconstruction. On the other hand, if there exists a gradient or edges or higher details within the edge, this would definitely affect the block decoding. The edges at the boundaries would not be continuous because of inadequate reconstruction.

The possibility of blockiness artifact increases with the decrease in the required output bit rate. The dependent frames, such as P or B frames, would be affected more severely if the I frame has been encoded or decoded with this artifact. A single blocky frame would not affect overall quality of the video, but a sequence of video would play an important part in deciding the quality.

There are video quality issues that are related to signal issues, such as RGB gamut and signal levels. Video data is captured and preprocessed as per the specified levels for color components so that the signal voltages representing these signals do not exceed the specified levels. The captured and preprocessed data is then passed to encoding systems for compression. The captured RGB data has to follow specified RGB color space called Gamut. The data as captured in RGB format is converted to YUV space as input to encoding systems. Because of loss of information and some processing of data by the encoder, the YUV data could be different from the original data as captured. This would lead to improper relationship among each of the luminance and chrominance components. The improper red, green, and blue components may become out-of-gamut. Similarly, YUV data can also be out of range as per the specified limits. But, RGB gamut and signal level issues cannot be manually detected and would require an automated system to scan each of the decoded YUV values as well as the converted RGB space.

There are issues where the encoded stream does not comply with the recommendation or common standards for encoding and decoding a stream. Non-conformance to specifications can be a result of encoding systems or transmission bit errors. Non-conformance also needs to be verified as it can lead to erroneous video output or may lead to crashes in the decoding systems.

A recent development in validating video quality is to conform to various guidelines for detection of flashing and regular patterns in video by ITU, ISO, and ITC. These guidelines are circulated for broadcasters to avoid harmful flashing video and patterns that had affected many cartoon viewers with ’Photosensitive Epilepsy’ in Japan. A couple of years ago in Japan, nearly 700 children were hospitalized after viewing a cartoon sequence of .Pokemon. series. These photosensitive epileptic children were affected by seizures as triggered by rapid scene changes, flashing images and some specific color patterns.

Medical experts examined these harmful video sequences and found that some specific types of spatial and temporal characteristics of video sequences were responsible for the harmful seizures. Based on the study of given videos, the Japanese and UK governments formulated guidelines for broadcasters to restrict video sequences containing any kind of harmful video flashes and patterns. Various organizations and forums such as ITU, ISO, and ITC formed recommendations specifying concrete thresholds and restrictions on the temporal and spatial characteristics of video content. It is quite difficult for a normal viewer to find out if any video contains the harmful flashes. The detection is only possible if an epileptic person is viewing the video.

The Requirement of Automated QC

File based systems in the above workflow have made the automation systems work efficiently. But, with the file-based systems, there is increased challenge of processing and delivering content faster, with competitive quality, and fulfillment of expectations.

On the other hand, the end-user has been provided with a choice of devices and media for viewing. HDTV represents a major advancement for end user experience compared to the existing SDTV video. In this case, broadcasters need to be more concerned about the higher media quality expectations of end user.

The content provider may provide the best quality media to the broadcasters. However, all the conversions and transformations leading up to media delivery make it important for broadcasters to maintain the end user media quality.

The human eyes often cannot perceive the inherent errors in a video frame, for example - RGB color gamut, video signal levels, width of bars, or expected standard of color bar. The detection of these errors requires some computations that the human eye cannot validate just by viewing a frame.

Manual inspection is useful in cases where human eyes can perceive the defects in video frames, such as blockiness and blurriness. However, manual inspection can only judge one frame at a time. Manual inspection cannot judge the overall quality degradation in objective terms. The quality index provided by personnel varies based on skill, experience, and individual preference. Thus a formalized, computational method is required for an objective and measurable quality feedback.

Since there are numerous file formats and delivery formats, manual validation would tend to become increasingly error prone with the increase in information to be validated for each of the media essence. The fast pace of new formats or guidelines coming into the industry necessitates constant re-training of the personnel. This involves cost and time, but still leaves scope for uncertainties in the quality of media.

Therefore, media validation needs to be automated using an intelligent and flexible environment that can process huge volumes of data in an accurate and consistent manner. This system would be parameterized with the required expectations and rules of validating the media and be aware of various media formats, conformance rules for compression formats, recommendations, guidelines of various standards, and other complex media attributes. The system would rely on processes and algorithms to detect the quality of a frame or multitude of frames in an objective manner and correlate it with the human experience for video quality.

Take the case of a 1-hour media file containing audio and video. A manual process would take at least 1-hour at each of the stages of the workflow to check against a defined set of specifications. Also, multiple specification sets may require checking of the entire media multiple times. In the worst case any change in requirement would require the whole process to be repeated again. Additionally, the audio and video data has to be processed separately. The validation process would require utmost attention and complete knowledge about the requirements or specifications.

On the other hand, an automated system can operate on a 24x7 basis for such a validation process, giving accurate and consistent results irrespective of the amount of data to be processed. This system can operate in parallel to all the stages of the workflow, thus saving time. Detailed specifications and guidelines for all compression formats and delivery formats can be part of the knowledge base of the automated system. In case of the automation system working in real time, a validation report can be provided in just an hour, thus saving time and costs.

A sample workflow with the automated content verification system checking media quality at various stages is illustrated in Figure 2.

Conclusion

The issues and complexities involved in file-based broacast workflows necessitate the adoption of automated content verification for video and audio quality.

Visual or manual inspection of media content invariably fails in identifying problems and cannot easily scale for large media volumes and complex specifications. As manual checks are inconsistent, subjective, and dependent on individual skills, absolute dependence on manual quality checks cannot justify return on investment.

The adoption of automated content verification is the only way to fulfill the expectations of consumers and achieve a competitive edge in the media market.

 

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