Fast Mode Decision for 3D-HEVC Depth Intracoding

The emerging international standard of high efficiency video coding based 3D video coding (3D-HEVC) is a successor to multiview video coding (MVC). In 3D-HEVC depth intracoding, depth modeling mode (DMM) and high efficiency video coding (HEVC) intraprediction mode are both employed to select the best coding mode for each coding unit (CU). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs the 3D-HEVC from practical application. In this paper, a fast mode decision algorithm based on the correlation between texture video and depth map is proposed to reduce 3D-HEVC depth intracoding computational complexity. Since the texture video and its associated depth map represent the same scene, there is a high correlation among the prediction mode from texture video and depth map. Therefore, we can skip some specific depth intraprediction modes rarely used in related texture CU. Experimental results show that the proposed algorithm can significantly reduce computational complexity of 3D-HEVC depth intracoding while maintaining coding efficiency

Motion Vector Sharing and Bitrate Allocation for 3D Video-Plus-Depth Coding

The video-plus-depth data representation uses a regular texture video enriched with the so-called depth map, providing the depth distance for each pixel. The compression efficiency is usually higher for smooth, gray level data representing the depth map than for classical video texture. However, improvements of the coding efficiency are still possible, taking into account the fact that the video and the depth map sequences are strongly correlated. Classically, the correlation between the texture motion vectors and the depth map motion vectors is not exploited in the coding process. The aim of this paper is to reduce the amount of information for describing the motion of the texture video and of the depth map sequences by sharing one common motion vector field. Furthermore, in the literature, the bitrate control scheme generally fixes for the depth map sequence a percentage of 20% of the texture stream bitrate. However, this fixed percentage can affect the depth coding efficiency, and it should also depend on the content of each sequence. We propose a new bitrate allocation strategy between the texture and its associated per-pixel depth information. We provide comparative analysis to measure the quality of the resulting 3D+t sequences

Quality of Experience in Immersive Video Technologies

Over the last decades, several technological revolutions have impacted the television industry, such as the shifts from black & white to color and from standard to high-definition. Nevertheless, further considerable improvements can still be achieved to provide a better multimedia experience, for example with ultra-high-definition, high dynamic range & wide color gamut, or 3D. These so-called immersive technologies aim at providing better, more realistic, and emotionally stronger experiences. To measure quality of experience (QoE), subjective evaluation is the ultimate means since it relies on a pool of human subjects. However, reliable and meaningful results can only be obtained if experiments are properly designed and conducted following a strict methodology. In this thesis, we build a rigorous framework for subjective evaluation of new types of image and video content. We propose different procedures and analysis tools for measuring QoE in immersive technologies. As immersive technologies capture more information than conventional technologies, they have the ability to provide more details, enhanced depth perception, as well as better color, contrast, and brightness. To measure the impact of immersive technologies on the viewersâ QoE, we apply the proposed framework for designing experiments and analyzing collected subjectsâ ratings. We also analyze eye movements to study human visual attention during immersive content playback. Since immersive content carries more information than conventional content, efficient compression algorithms are needed for storage and transmission using existing infrastructures. To determine the required bandwidth for high-quality transmission of immersive content, we use the proposed framework to conduct meticulous evaluations of recent image and video codecs in the context of immersive technologies. Subjective evaluation is time consuming, expensive, and is not always feasible. Consequently, researchers have developed objective metrics to automatically predict quality. To measure the performance of objective metrics in assessing immersive content quality, we perform several in-depth benchmarks of state-of-the-art and commonly used objective metrics. For this aim, we use ground truth quality scores, which are collected under our subjective evaluation framework. To improve QoE, we propose different systems for stereoscopic and autostereoscopic 3D displays in particular. The proposed systems can help reducing the artifacts generated at the visualization stage, which impact picture quality, depth quality, and visual comfort. To demonstrate the effectiveness of these systems, we use the proposed framework to measure viewersâ preference between these systems and standard 2D & 3D modes. In summary, this thesis tackles the problems of measuring, predicting, and improving QoE in immersive technologies. To address these problems, we build a rigorous framework and we apply it through several in-depth investigations. We put essential concepts of multimedia QoE under this framework. These concepts not only are of fundamental nature, but also have shown their impact in very practical applications. In particular, the JPEG, MPEG, and VCEG standardization bodies have adopted these concepts to select technologies that were proposed for standardization and to validate the resulting standards in terms of compression efficiency