Error-resilient multi-view video plus depth based 3-D video coding

Three Dimensional (3-D) video, by definition, is a collection of signals that can provide depth perception of a 3-D scene. With the development of 3-D display technologies and interactive multimedia systems, 3-D video has attracted significant interest from both industries and academia with a variety of applications. In order to provide desired services in various 3-D video applications, the multiview video plus depth (MVD) representation, which can facilitate the generation of virtual views, has been determined to be the best format for 3-D video data. Similar to 2-D video, compressed 3-D video is highly sensitive to transmission errors due to errors propagated from the current frame to the future predicted frames. Moreover, since the virtual views required for auto-stereoscopic displays are rendered from the compressed texture videos and depth maps, transmission errors of the distorted texture videos and depth maps can be further propagated to the virtual views. Besides, the distortions in texture and depth show different effects on the rendering views. Therefore, compared to the reliability of the transmission of the 2-D video, error-resilient texture video and depth map coding are facing major new challenges. This research concentrates on improving the error resilience performance of MVD-based 3-D video in packet loss scenarios. Based on the analysis of the propagating behaviour of transmission errors, a Wyner-Ziv (WZ)-based error-resilient algorithm is first designed for coding of the multi-view video data or depth data. In this scheme, an auxiliary redundant stream encoded according to WZ principle is employed to protect a primary stream encoded with standard multi-view video coding codec. Then, considering the fact that different combinations of texture and depth coding mode will exhibit varying robustness to transmission errors, a rate-distortion optimized mode switching scheme is proposed to strike the optimal trade-off between robustness and compression effciency. In this approach, the texture and depth modes are jointly optimized by minimizing the overall distortion of both the coded and synthesized views subject to a given bit rate. Finally, this study extends the research on the reliable transmission of view synthesis prediction (VSP)-based 3-D video. In order to mitigate the prediction position error caused by packet losses in the depth map, a novel disparity vector correction algorithm is developed, where the corrected disparity vector is calculated from the depth error. To facilitate decoder error concealment, the depth error is recursively estimated at the decoder. The contributions of this dissertation are multifold. First, the proposed WZbased error-resilient algorithm can accurately characterize the effect of transmission error on multi-view distortion at the transform domain in consideration of both temporal and inter-view error propagation, and based on the estimated distortion, this algorithm can perform optimal WZ bit allocation at the encoder through explicitly developing a sophisticated rate allocation strategy. This proposed algorithm is able to provide a finer granularity in performing rate adaptivity and unequal error protection for multi-view data, not only at the frame level, but also at the bit-plane level. Secondly, in the proposed mode switching scheme, a new analytic model is formulated to optimally estimate the view synthesis distortion due to packet losses, in which the compound impact of the transmission distortions of both the texture video and the depth map on the quality of the synthesized view is mathematically analysed. The accuracy of this view synthesis distortion model is demonstrated via simulation results and, further, the estimated distortion is integrated into a rate-distortion framework for optimal mode switching to achieve substantial performance gains over state-of-the-art algorithms. Last, but not least, this dissertation provides a preliminary investigation of VSP-based 3-D video over unreliable channel. In the proposed disparity vector correction algorithm, the pixel-level depth map error can be precisely estimated at the decoder without the deterministic knowledge of the error-free reconstructed depth. The approximation of the innovation term involved in depth error estimation is proved theoretically. This algorithm is very useful to conceal the position-erroneous pixels whose disparity vectors are correctly received

Rate-Distortion Analysis of Multiview Coding in a DIBR Framework

Depth image based rendering techniques for multiview applications have been recently introduced for efficient view generation at arbitrary camera positions. Encoding rate control has thus to consider both texture and depth data. Due to different structures of depth and texture images and their different roles on the rendered views, distributing the available bit budget between them however requires a careful analysis. Information loss due to texture coding affects the value of pixels in synthesized views while errors in depth information lead to shift in objects or unexpected patterns at their boundaries. In this paper, we address the problem of efficient bit allocation between textures and depth data of multiview video sequences. We adopt a rate-distortion framework based on a simplified model of depth and texture images. Our model preserves the main features of depth and texture images. Unlike most recent solutions, our method permits to avoid rendering at encoding time for distortion estimation so that the encoding complexity is not augmented. In addition to this, our model is independent of the underlying inpainting method that is used at decoder. Experiments confirm our theoretical results and the efficiency of our rate allocation strategy

Loss-resilient Coding of Texture and Depth for Free-viewpoint Video Conferencing

Free-viewpoint video conferencing allows a participant to observe the remote 3D scene from any freely chosen viewpoint. An intermediate virtual viewpoint image is commonly synthesized using two pairs of transmitted texture and depth maps from two neighboring captured viewpoints via depth-image-based rendering (DIBR). To maintain high quality of synthesized images, it is imperative to contain the adverse effects of network packet losses that may arise during texture and depth video transmission. Towards this end, we develop an integrated approach that exploits the representation redundancy inherent in the multiple streamed videos a voxel in the 3D scene visible to two captured views is sampled and coded twice in the two views. In particular, at the receiver we first develop an error concealment strategy that adaptively blends corresponding pixels in the two captured views during DIBR, so that pixels from the more reliable transmitted view are weighted more heavily. We then couple it with a sender-side optimization of reference picture selection (RPS) during real-time video coding, so that blocks containing samples of voxels that are visible in both views are more error-resiliently coded in one view only, given adaptive blending will erase errors in the other view. Further, synthesized view distortion sensitivities to texture versus depth errors are analyzed, so that relative importance of texture and depth code blocks can be computed for system-wide RPS optimization. Experimental results show that the proposed scheme can outperform the use of a traditional feedback channel by up to 0.82 dB on average at 8% packet loss rate, and by as much as 3 dB for particular frames

Optimization of Occlusion-Inducing Depth Pixels in 3-D Video Coding

The optimization of occlusion-inducing depth pixels in depth map coding has received little attention in the literature, since their associated texture pixels are occluded in the synthesized view and their effect on the synthesized view is considered negligible. However, the occlusion-inducing depth pixels still need to consume the bits to be transmitted, and will induce geometry distortion that inherently exists in the synthesized view. In this paper, we propose an efficient depth map coding scheme specifically for the occlusion-inducing depth pixels by using allowable depth distortions. Firstly, we formulate a problem of minimizing the overall geometry distortion in the occlusion subject to the bit rate constraint, for which the depth distortion is properly adjusted within the set of allowable depth distortions that introduce the same disparity error as the initial depth distortion. Then, we propose a dynamic programming solution to find the optimal depth distortion vector for the occlusion. The proposed algorithm can improve the coding efficiency without alteration of the occlusion order. Simulation results confirm the performance improvement compared to other existing algorithms

Depth map compression via 3D region-based representation

In 3D video, view synthesis is used to create new virtual views between encoded camera views. Errors in the coding of the depth maps introduce geometry inconsistencies in synthesized views. In this paper, a new 3D plane representation of the scene is presented which improves the performance of current standard video codecs in the view synthesis domain. Two image segmentation algorithms are proposed for generating a color and depth segmentation. Using both partitions, depth maps are segmented into regions without sharp discontinuities without having to explicitly signal all depth edges. The resulting regions are represented using a planar model in the 3D world scene. This 3D representation allows an efficient encoding while preserving the 3D characteristics of the scene. The 3D planes open up the possibility to code multiview images with a unique representation.Postprint (author's final draft

Optimized Data Representation for Interactive Multiview Navigation

In contrary to traditional media streaming services where a unique media content is delivered to different users, interactive multiview navigation applications enable users to choose their own viewpoints and freely navigate in a 3-D scene. The interactivity brings new challenges in addition to the classical rate-distortion trade-off, which considers only the compression performance and viewing quality. On the one hand, interactivity necessitates sufficient viewpoints for richer navigation; on the other hand, it requires to provide low bandwidth and delay costs for smooth navigation during view transitions. In this paper, we formally describe the novel trade-offs posed by the navigation interactivity and classical rate-distortion criterion. Based on an original formulation, we look for the optimal design of the data representation by introducing novel rate and distortion models and practical solving algorithms. Experiments show that the proposed data representation method outperforms the baseline solution by providing lower resource consumptions and higher visual quality in all navigation configurations, which certainly confirms the potential of the proposed data representation in practical interactive navigation systems