Compression and Subjective Quality Assessment of 3D Video

In recent years, three-dimensional television (3D TV) has been broadly considered as the successor to the existing traditional two-dimensional television (2D TV) sets. With its capability of offering a dynamic and immersive experience, 3D video (3DV) is expected to expand conventional video in several applications in the near future. However, 3D content requires more than a single view to deliver the depth sensation to the viewers and this, inevitably, increases the bitrate compared to the corresponding 2D content. This need drives the research trend in video compression field towards more advanced and more efficient algorithms. Currently, the Advanced Video Coding (H.264/AVC) is the state-of-the-art video coding standard which has been developed by the Joint Video Team of ISO/IEC MPEG and ITU-T VCEG. This codec has been widely adopted in various applications and products such as TV broadcasting, video conferencing, mobile TV, and blue-ray disc. One important extension of H.264/AVC, namely Multiview Video Coding (MVC) was an attempt to multiple view compression by taking into consideration the inter-view dependency between different views of the same scene. This codec H.264/AVC with its MVC extension (H.264/MVC) can be used for encoding either conventional stereoscopic video, including only two views, or multiview video, including more than two views. In spite of the high performance of H.264/MVC, a typical multiview video sequence requires a huge amount of storage space, which is proportional to the number of offered views. The available views are still limited and the research has been devoted to synthesizing an arbitrary number of views using the multiview video and depth map (MVD). This process is mandatory for auto-stereoscopic displays (ASDs) where many views are required at the viewer side and there is no way to transmit such a relatively huge number of views with currently available broadcasting technology. Therefore, to satisfy the growing hunger for 3D related applications, it is mandatory to further decrease the bitstream by introducing new and more efficient algorithms for compressing multiview video and depth maps. This thesis tackles the 3D content compression targeting different formats i.e. stereoscopic video and depth-enhanced multiview video. Stereoscopic video compression algorithms introduced in this thesis mostly focus on proposing different types of asymmetry between the left and right views. This means reducing the quality of one view compared to the other view aiming to achieve a better subjective quality against the symmetric case (the reference) and under the same bitrate constraint. The proposed algorithms to optimize depth-enhanced multiview video compression include both texture compression schemes as well as depth map coding tools. Some of the introduced coding schemes proposed for this format include asymmetric quality between the views. Knowing that objective metrics are not able to accurately estimate the subjective quality of stereoscopic content, it is suggested to perform subjective quality assessment to evaluate different codecs. Moreover, when the concept of asymmetry is introduced, the Human Visual System (HVS) performs a fusion process which is not completely understood. Therefore, another important aspect of this thesis is conducting several subjective tests and reporting the subjective ratings to evaluate the perceived quality of the proposed coded content against the references. Statistical analysis is carried out in the thesis to assess the validity of the subjective ratings and determine the best performing test cases

No-reference depth map quality evaluation model based on depth map edge confidence measurement in immersive video applications

When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance

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

Real-time video-plus-depth content creation utilizing time-of-flight sensor - from capture to display

Recent developments in 3D camera technologies, display technologies and other related fields have been aiming to provide 3D experience for home user and establish services such as Three-Dimensional Television (3DTV) and Free-Viewpoint Television (FTV). Emerging multiview autostereoscopic displays do not require any eyewear and can be watched by multiple users at the same time, thus are very attractive for home environment usage. To provide a natural 3D impression, autostereoscopic 3D displays have been design to synthesize multi-perspective virtual views of a scene using Depth-Image-Based Rendering (DIBR) techniques. One key issue of DIBR is that scene depth information in a form of a depth map is required in order to synthesize virtual views. Acquiring this information is quite complex and challenging task and still an active research topic. In this thesis, the problem of dynamic 3D video content creation of real-world visual scenes is addressed. The work assumed data acquisition setting including Time-of-Flight (ToF) depth sensor and a single conventional video camera. The main objective of the work is to develop efficient algorithms for the stages of synchronous data acquisition, color and ToF data fusion, and final view-plus-depth frame formatting and rendering. The outcome of this thesis is a prototype 3DTV system capable for rendering live 3D video on a 3D autostereoscopic display. The presented system makes extensive use of the processing capabilities of modern Graphics Processing Units (GPUs) in order to achieve real-time processing rates while providing an acceptable visual quality. Furthermore, the issue of arbitrary view synthesis is investigated in the context of DIBR and a novel approach based on depth layering is proposed. The proposed approach is applicable for general virtual views synthesis, i.e. in terms of different camera parameters such as position, orientation, focal length and varying sensors spatial resolutions. The experimental results demonstrate real-time capability of the proposed method even for CPU-based implementations. It compares favorably to other view synthesis methods in terms of visual quality, while being more computationally efficient

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

Dense light field coding: a survey

Light Field (LF) imaging is a promising solution for providing more immersive and closer to reality multimedia experiences to end-users with unprecedented creative freedom and flexibility for applications in different areas, such as virtual and augmented reality. Due to the recent technological advances in optics, sensor manufacturing and available transmission bandwidth, as well as the investment of many tech giants in this area, it is expected that soon many LF transmission systems will be available to both consumers and professionals. Recognizing this, novel standardization initiatives have recently emerged in both the Joint Photographic Experts Group (JPEG) and the Moving Picture Experts Group (MPEG), triggering the discussion on the deployment of LF coding solutions to efficiently handle the massive amount of data involved in such systems. Since then, the topic of LF content coding has become a booming research area, attracting the attention of many researchers worldwide. In this context, this paper provides a comprehensive survey of the most relevant LF coding solutions proposed in the literature, focusing on angularly dense LFs. Special attention is placed on a thorough description of the different LF coding methods and on the main concepts related to this relevant area. Moreover, comprehensive insights are presented into open research challenges and future research directions for LF coding.info:eu-repo/semantics/publishedVersio