Nick Vercammen

No-Reference Bitstream-Based Visual Quality Impairment Detection for High Definition H.264/AVC Encoded Video Sequences

Ensuring and maintaining adequate Quality of Experience towards end-users are key objectives for video service providers, not only for increasing customer satisfaction but also as service differentiator. However, in the case of High Definition video streaming over IP-based networks, network impairments such as packet loss can severely degrade the perceived visual quality. Several standard organizations have established a minimum set of performance objectives which should be achieved for obtaining satisfactory quality. Therefore, video service providers should continuously monitor the network and the quality of the received video streams in order to detect visual degradations. Objective video quality metrics enable automatic measurement of perceived quality. Unfortunately, the most reliable metrics require access to both the original and the received video streams which makes them inappropriate for real-time monitoring. In this article, we present a novel no-reference bitstream-based visual quality impairment detector which enables real-time detection of visual degradations caused by network impairments. By only incorporating information extracted from the encoded bitstream, network impairments are classified as visible or invisible to the end-user. Our results show that impairment visibility can be classified with a high accuracy which enables real-time validation of the existing performance objectives.

ViQID: A No-Reference bit stream-based visual quality impairment detector

In order to ensure adequate quality towards the end users at all time, video service providers are getting more interested in monitoring their video streams. Objective video quality metrics provide a means of measuring (audio)visual quality in an automated manner. Unfortunately, most of the current existing metrics cannot be used for real-time monitoring due to their dependencies on the original video sequence. In this paper we present a new objective video quality metric which classifies packet loss as visible or invisible based on information extracted solely from the captured encoded H.264/AVC video bit stream. Our results show that the visibility of packet loss can be predicted with a high accuracy, without the need for deep packet inspection. This enables service providers to monitor quality in real-time.

xStreamer: modular multimedia streaming

The xStreamer intends to be a flexible and modular open source streamer. The selection of current open source streamers which support both video and audio is limited, with VLC Media Player, Darwin Streaming Server and Helix DNA Server being the foremost solutions. The xStreamer distinguishes itself by providing a modularity that goes beyond the mere modular programming offered by the current open source solutions and that manifests itself in how the user controls and configures the streamer.

Assessing the importance of audio/video synchronization for simultaneous translation of video sequences

Lip synchronization is considered a key parameter during interactive communication. In the case of video conferencing and television broadcasting, the differential delay between audio and video should remain below certain thresholds, as recommended by several standardization bodies. However, further research has also shown that these thresholds can be relaxed, depending on the targeted application and use case. In this article, we investigate the influence of lip sync on the ability to perform real-time language interpretation during video conferencing. Furthermore, we are also interested in determining proper lip sync visibility thresholds applicable to this use case. Therefore, we conducted a subjective experiment using expert interpreters, which were required to perform a simultaneous translation, and non-experts. Our results show that significant differences are obtained when conducting subjective experiments with expert interpreters. As interpreters are primarily focused on performing the simultaneous translation, lip sync detectability thresholds are higher compared with existing recommended thresholds. As such, primary focus and the targeted application and use case are important factors to be considered when selecting proper lip sync acceptability thresholds.

Extensive video quality evaluation: A scalable video testing platform

With the advent of new upcoming online video services such as IPTV, video on demand (VoD) and peer-to-peer (P2P) video streaming, content providers are gaining more and more interest in measuring and monitoring video quality as perceived by end-users; also known as quality of experience (QoE). Objective video quality metrics provide a means of measuring visual quality degradations but in order to be able to measure QoE, these objective metrics should incorporate all quality affecting parameters such as encoding bitrate, network impairments and error concealment techniques. As a consequence, in order to construct or validate a proper objective video quality metric, extensive video evaluation tests must be performed. In this paper we present a scalable video testing platform that simplifies the management and execution of such video quality evaluation tests. Results indicate that the use of our testing platform drastically reduces overall experiment duration.

Comparing objective visual quality impairment detection in 2D and 3D video sequences

Thanks to the availability of 3D-capable televisions and bluray players, 3D content is made accessible in the home. Recently, an extension of the H.264/AVC video coding standard has been defined for encoding 3D video content. This extension, called Multiview Video Coding, allows inter-view prediction resulting in a better compression efficiency. However, due to these inter-view dependencies impairments in one view caused by e.g. packet losses can lead to degradations in other views. Research has already been conducted towards estimating packet loss visibility in H.264/AVC encoded sequences. In this paper, we investigate the possibility of using an existing decision tree-based classifier for estimating impairment visibility in 3D MVC encoded sequences. Our results show that, in the case of losing entire pictures, it is possible to estimate packet loss visibility in 3D MVC encoded sequences with a high accuracy by only taking into account a limited number of parameters.