Fast video transcoding from H.263 to H.264/MPEG-4 AVC

In the past 10 years detailed works on different video transcoders have been published. However, the new ITU-T Recommendation H.264—also adapted as ISO/IEC MPEG-4 Part 10 (AVC)—provides many new encoding options for the prediction processes that lead to difficulties for low complexity transcoding. In this work we present very fast transcoding techniques to convert H.263 bitstreams into H.264/AVC bitstreams. We will give reasoning, why the proposed pixel domain approach is advantageous in this scenario instead of using a DCT domain transcoder. Our approach results in less than 9% higher data rate at equivalent PSNR quality compared to a full-search approach. But this rate loss allows the reduction of the search complexity by a factor of over 200 for inter frames and still a reduction of over 70% for intra frames. A comparison to a fast search algorithm is given. We also provide simulation results that our algorithm works for transcoding MPEG-2 to H.264/AVC in the aimed scenario.

Modeling and estimating the subjects’ diversity of opinions in video quality assessment: a neural network based approach

Subjective experiments are considered the most reliable way to assess the perceived visual quality. However, observers’ opinions are characterized by large diversity: in fact, even the same observer is often not able to exactly repeat his first opinion when rating again a given stimulus. This makes the Mean Opinion Score (MOS) alone, in many cases, not sufficient to get accurate information about the perceived visual quality. To this aim, it is important to have a measure characterizing to what extent the observed or predicted MOS value is reliable and stable. For instance, the Standard deviation of the Opinions of the Subjects (SOS) could be considered as a measure of reliability when evaluating the quality subjectively. However, we are not aware of the existence of models or algorithms that allow to objectively predict how much diversity would be observed in subjects’ opinions in terms of SOS. In this work we observe, on the basis of a statistical analysis made on several subjective experiments, that the disagreement between the quality as measured by means of different objective video quality metrics (VQMs) can provide information on the diversity of the observers’ ratings on a given processed video sequence (PVS). In light of this observation we: i) propose and validate a model for the SOS observed in a subjective experiment; ii) design and train Neural Networks (NNs) that predict the average diversity that would be observed among the subjects’ ratings for a PVS starting from a set of VQMs values computed on such a PVS; iii) give insights into how the same NN based approach can be used to identify potential anomalies in the data collected in subjective experiments.

     

How visual fatigue and discomfort impact 3D-TV quality of experience: a comprehensive review of technological, psychophysical, and psychological factors

The quality of experience (QoE) of 3D contents is usually considered to be the combination of the perceived visual quality, the perceived depth quality, and lastly the visual fatigue and comfort. When either fatigue or discomfort are induced, studies tend to show that observers prefer to experience a 2D version of the contents. For this reason, providing a comfortable experience is a prerequisite for observers to actually consider the depth effect as a visualization improvement. In this paper, we propose a comprehensive review on visual fatigue and discomfort induced by the visualization of 3D stereoscopic contents, in the light of physiological and psychological processes enabling depth perception. First, we review the multitude of manifestations of visual fatigue and discomfort (near triad disorders, symptoms for discomfort), as well as means for detection and evaluation. We then discuss how, in 3D displays, ocular and cognitive conflicts with real world experience may cause fatigue and discomfort; these includes the accommodation–vergence conflict, the inadequacy between presented stimuli and observers depth of focus, and the cognitive integration of conflicting depth cues. We also discuss some limits for stereopsis that constrain our ability to perceive depth, and in particular the perception of planar and in-depth motion, the limited fusion range, and various stereopsis disorders. Finally, this paper discusses how the different aspects of fatigue and discomfort apply to 3D technologies and contents. We notably highlight the need for respecting a comfort zone and avoiding camera and rendering artifacts. We also discuss the influence of visual attention, exposure duration, and training. Conclusions provide guidance for best practices and future research.     

Methodologies for Assessing 3D QoE:Standards and Explorative Studies

Mastering quality of experience (QoE) is key to the widespread adoption of stereoscopic 3DTV (S-3DTV). However, assessing QoE of S-3DTV is not straightforward. Methods for determining observer experience need to be clearly defined and sufficiently robust. In this paper, we present state-of-the-art subjective QoE assessment for S-3DTV. We present conventional standardized ITU recommendations for evaluating picture quality and discuss new ITU activities in the area of S-3DTV assessment. We also present and discuss explorative studies from the literature. We then introduce ways of using conventional quality assessment for S-3DTV QoE assessment. In discussing our proposal, we mainly focus on QoE indicators and common features of subjective assessment. Multidimensional QoE indicators need to be used in S-3DTV to highlight advantages and reveal problems. In the second part of our proposal, we discuss the requirements for adapting ITU-R BT.500, a conventional subjective QoE assessment method, ITU-R BT.500, for assessing QoE of S-3DTV are presented.     

Proof-of-concept: role of generic content characteristics in optimizing video encoders

The influence of content characteristics on the efficiency of redundancy and irrelevance reduction in video coding is well known. Each new standard in video coding includes additional coding tools that potentially increase the complexity of the encoding process in order to gain further rate-distortion efficiency. In order to be versatile, encoder implementations often neglect the content dependency or they optimize the encoding complexity on a local scale, i.e. on a single frame or on the coding unit level without being aware of the global content type. In this contribution, an analysis is presented which coding tool settings of the recent High Efficiency Video Coding (HEVC) standard are most efficient for a given content type when balancing rate-distortion against computational complexity measured in encoding time. The content type is algorithmically determined, leading to a framework for rate-distortion-complexity based encoder parameter decision for any given video sequence. The implementability is demonstrated using a set of 35 Ultra-HD (UHD) sequences. The performance results and evaluations show that the encoding parameters may be predicted to optimize the video coding. For instance, predicting motion search range achieves complexity reduction of 36% on average when HEVC reference HM is used at a cost of bitrate (2%). When another HEVC coding standard software, x265, is used to predict the coding unit (CU) size, there is a reduction of 20% in bitrate and of 8% in distortion but there is a reduction of 6% in execution time.