End-to-end 3D video communication over heterogeneous networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Three-dimensional technology, more commonly referred to as 3D technology, has revolutionised many fields including entertainment, medicine, and communications to name a few. In addition to 3D films, games, and sports channels, 3D perception has made tele-medicine a reality. By the year 2015, 30% of the all HD panels at home will be 3D enabled, predicted by consumer electronics manufacturers. Stereoscopic cameras, a comparatively mature technology compared to other 3D systems, are now being used by ordinary citizens to produce 3D content and share at a click of a button just like they do with the 2D counterparts via sites like YouTube. But technical challenges still exist, including with autostereoscopic multiview displays. 3D content requires many complex considerations--including how to represent it, and deciphering what is the best compression format--when considering transmission or storage, because of its increased amount of data. Any decision must be taken in the light of the available bandwidth or storage capacity, quality and user expectations. Free viewpoint navigation also remains partly unsolved. The most pressing issue getting in the way of widespread uptake of consumer 3D systems is the ability to deliver 3D content to heterogeneous consumer displays over the heterogeneous networks. Optimising 3D video communication solutions must consider the entire pipeline, starting with optimisation at the video source to the end display and transmission optimisation. Multi-view offers the most compelling solution for 3D videos with motion parallax and freedom from wearing headgear for 3D video perception. Optimising multi-view video for delivery and display could increase the demand for true 3D in the consumer market. This thesis focuses on an end-to-end quality optimisation in 3D video communication/transmission, offering solutions for optimisation at the compression, transmission, and decoder levels.Brunel University - Isambard Research Scholarshi

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

Impact of packet losses in scalable 3D holoscopic video coding

Holoscopic imaging became a prospective glassless 3D technology to provide more natural 3D viewing experiences to the end user. Additionally, holoscopic systems also allow new post-production degrees of freedom, such as controlling the plane of focus or the viewing angle presented to the user. However, to successfully introduce this technology into the consumer market, a display scalable coding approach is essential to achieve backward compatibility with legacy 2D and 3D displays. Moreover, to effectively transmit 3D holoscopic content over error-prone networks, e.g., wireless networks or the Internet, error resilience techniques are required to mitigate the impact of data impairments in the user quality perception. Therefore, it is essential to deeply understand the impact of packet losses in terms of decoding video quality for the specific case of 3D holoscopic content, notably when a scalable approach is used. In this context, this paper studies the impact of packet losses when using a three-layer display scalable 3D holoscopic video coding architecture previously proposed, where each layer represents a different level of display scalability (i.e., L0 - 2D, L1 - stereo or multiview, and L2 - full 3D holoscopic). For this, a simple error concealment algorithm is used, which makes use of inter-layer redundancy between multiview and 3D holoscopic content and the inherent correlation of the 3D holoscopic content to estimate lost data. Furthermore, a study of the influence of 2D views generation parameters used in lower layers on the performance of the used error concealment algorithm is also presented.info:eu-repo/semantics/acceptedVersio

Low Complexity Multiview Video Coding

3D video is a technology that has seen a tremendous attention in the recent years. Multiview Video Coding (MVC) is an extension of the popular H.264 video coding standard and is commonly used to compress 3D videos. It offers an improvement of 20% to 50% in compression efficiency over simulcast encoding of multiview videos using the conventional H.264 video coding standard. However, there are two important problems associated with it: (i) its superior compression performance comes at the cost of significantly higher computational complexity which hampers the real-world realization of MVC encoder in applications such as 3D live broadcasting and interactive Free Viewpoint Television (FTV), and (ii) compressed 3D videos can suffer from packet loss during transmission, which can degrade the viewing quality of the 3D video at the decoder. This thesis aims to solve these problems by presenting techniques to reduce the computational complexity of the MVC encoder and by proposing a consistent error concealment technique for frame losses in 3D video transmission. The thesis first analyses the complexity of the MVC encoder. It then proposes two novel techniques to reduce the complexity of motion and disparity estimation. The first method achieves complexity reduction in the disparity estimation process by exploiting the relationship between temporal levels, type of macroblocks and search ranges while the second method achieves it by exploiting the geometrical relation- ship between motion and disparity vectors in stereo frames. These two methods are then combined with other state-of-the-art methods in a unique framework where gains add up. Experimental results show that the proposed low-complexity framework can reduce the encoding time of the standard MVC encoder by over 93% while maintaining similar compression efficiency performance. The addition of new View Synthesis Prediction (VSP) modes to the MVC encoding framework improves the compression efficiency of MVC. However, testing additional modes comes at the cost of increased encoding complexity. In order to reduce the encoding complexity, the thesis, next, proposes a bayesian early mode decision technique for a VSP enhanced MVC coder. It exploits the statistical similarities between the RD costs of the VSP SKIP mode in neighbouring views to terminate the mode decision process early. Results indicate that the proposed technique can reduce the encoding time of the enhanced MVC coder by over 33% at similar compression efficiency levels. Finally, compressed 3D videos are usually required to be broadcast to a large number of users where transmission errors can lead to frame losses which can degrade the video quality at the decoder. A simple reconstruction of the lost frames can lead to inconsistent reconstruction of the 3D scene which may negatively affect the viewing experience of a user. In order to solve this problem, the thesis proposes, at the end, a consistency model for recovering frames lost during transmission. The proposed consistency model is used to evaluate inter-view and temporal consistencies while selecting candidate blocks for concealment. Experimental results show that the proposed technique is able to recover the lost frames with high consistency and better quality than two standard error concealment methods and a baseline technique based on the boundary matching algorithm

3D multiple description coding for error resilience over wireless networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Mobile communications has gained a growing interest from both customers and service providers alike in the last 1-2 decades. Visual information is used in many application domains such as remote health care, video –on demand, broadcasting, video surveillance etc. In order to enhance the visual effects of digital video content, the depth perception needs to be provided with the actual visual content. 3D video has earned a significant interest from the research community in recent years, due to the tremendous impact it leaves on viewers and its enhancement of the user’s quality of experience (QoE). In the near future, 3D video is likely to be used in most video applications, as it offers a greater sense of immersion and perceptual experience. When 3D video is compressed and transmitted over error prone channels, the associated packet loss leads to visual quality degradation. When a picture is lost or corrupted so severely that the concealment result is not acceptable, the receiver typically pauses video playback and waits for the next INTRA picture to resume decoding. Error propagation caused by employing predictive coding may degrade the video quality severely. There are several ways used to mitigate the effects of such transmission errors. One widely used technique in International Video Coding Standards is error resilience. The motivation behind this research work is that, existing schemes for 2D colour video compression such as MPEG, JPEG and H.263 cannot be applied to 3D video content. 3D video signals contain depth as well as colour information and are bandwidth demanding, as they require the transmission of multiple high-bandwidth 3D video streams. On the other hand, the capacity of wireless channels is limited and wireless links are prone to various types of errors caused by noise, interference, fading, handoff, error burst and network congestion. Given the maximum bit rate budget to represent the 3D scene, optimal bit-rate allocation between texture and depth information rendering distortion/losses should be minimised. To mitigate the effect of these errors on the perceptual 3D video quality, error resilience video coding needs to be investigated further to offer better quality of experience (QoE) to end users. This research work aims at enhancing the error resilience capability of compressed 3D video, when transmitted over mobile channels, using Multiple Description Coding (MDC) in order to improve better user’s quality of experience (QoE). Furthermore, this thesis examines the sensitivity of the human visual system (HVS) when employed to view 3D video scenes. The approach used in this study is to use subjective testing in order to rate people’s perception of 3D video under error free and error prone conditions through the use of a carefully designed bespoke questionnaire.Petroleum Technology Development Fund (PTDF

Analysis and Comparison of Modern Video Compression Standards for Random-access Light-field Compression

Light-field (LF) 3D displays are anticipated to be the next-generation 3D displays by providing smooth motion parallax, wide field of view (FOV), and higher depth range than the current autostereoscopic displays. The projection-based multi-view LF 3D displays bring the desired new functionalities through a set of projection engines creating light sources for the continuous light field to be created. Such displays require a high number of perspective views as an input to fully exploit the visualization capabilities and viewing angle provided by the LF technology. Delivering, processing and de/compressing this amount of views pose big technical challenges. However, when processing light fields in a distributed system, access patterns in ray space are quite regular, some processing nodes do not need all views, moreover the necessary views are used only partially. This trait could be exploited by partial decoding of pictures to help providing less complex and thus real-time operation. However, none of the recent video coding standards (e.g., Advanced Video Coding (AVC)/H.264 and High Efficiency Video Coding (HEVC)/H.265 standards) provides partial decoding of video pictures. Such feature can be achieved by partitioning video pictures into partitions that can be processed independently at the cost of lowering the compression efficiency. Examples of such partitioning features introduced by the modern video coding standards include slices and tiles, which enable random access into the video bitstreams with a specific granularity. In addition, some extra requirements have to be imposed on the standard partitioning tools in order to be applicable in the context of partial decoding. This leads to partitions called self-contained which refers to isolated or independently decodable regions in the video pictures. This work studies the problem of creating self-contained partitions in the conventional AVC/H.264 and HEVC/H.265 standards, and HEVC 3D extensions including multi-view (i.e., MV-HEVC) and 3D (i.e., 3D-HEVC) extensions using slices and tiles, respectively. The requirements that need to be fulfilled in order to build self-contained partitions are described, and an encoder-side solution is proposed. Further, the work examines how slicing/tiling can be used to facilitate random access into the video bitstreams, how the number of slices/tiles affects the compression ratio considering different prediction structures, and how much effect partial decoding has on decoding time. Overall, the experimental results indicate that the finer the partitioning is, the higher the compression loss occurs. The usage of self-contained partitions makes the decoding operation very efficient and less complex

Adaptive intra refresh for robust wireless multi-view video

This thesis was submitted for the award of PhD and was awarded by Brunel University LondonMobile wireless communication technology is a fast developing field and every day new mobile communication techniques and means are becoming available. In this thesis multi-view video (MVV) is also refers to as 3D video. Thus, the 3D video signals through wireless communication are shaping telecommunication industry and academia. However, wireless channels are prone to high level of bit and burst errors that largely deteriorate the quality of service (QoS). Noise along the wireless transmission path can introduce distortion or make a compressed bitstream lose vital information. The error caused by noise progressively spread to subsequent frames and among multiple views due to prediction. This error may compel the receiver to pause momentarily and wait for the subsequent INTRA picture to continue decoding. The pausing of video stream affects the user's Quality of Experience (QoE). Thus, an error resilience strategy is needed to protect the compressed bitstream against transmission errors. This thesis focuses on error resilience Adaptive Intra Refresh (AIR) technique. The AIR method is developed to make the compressed 3D video more robust to channel errors. The process involves periodic injection of Intra-coded macroblocks in a cyclic pattern using H.264/AVC standard. The algorithm takes into account individual features in each macroblock and the feedback information sent by the decoder about the channel condition in order to generate an MVV-AIR map. MVV-AIR map generation regulates the order of packets arrival and identifies the motion activities in each macroblock. Based on the level of motion activity contained in each macroblock, the MVV-AIR map classifies frames as high or low motion macroblocks. A proxy MVV-AIR transcoder is used to validate the efficiency of the generated MVV-AIR map. The MVV-AIR transcoding algorithm uses spatial and views downscaling scheme to convert from MVV to single view. Various experimental results indicate that the proposed error resilient MVV-AIR transcoder technique effectively improves the quality of reconstructed 3D video in wireless networks. A comparison of MVV-AIR transcoder algorithm with some traditional error resilience techniques demonstrates that MVV-AIR algorithm performs better in an error prone channel. Results of simulation revealed significant improvements in both objective and subjective qualities. No additional computational complexity emanates from the scheme while the QoS and QoE requirements are still fully met.Tertiary Institution Trust Fund (TETFund) of Nigeri