Reducing 3D video coding complexity through more efficient disparity estimation

3D video coding for transmission exploits the Disparity Estimation (DE) to remove the inter-view redundancies present within both the texture and the depth map multi-view videos. Good estimation accuracy can be achieved by partitioning the macro-block into smaller subblocks partitions. However, the DE process must be performed on each individual sub-block to determine the optimal mode and their disparity vectors, in terms of ratedistortion efficiency. This vector estimation process is heavy on computational resources, thus, the coding computational cost becomes proportional to the number of search points and the inter-view modes tested during the rate-distortion optimization. In this paper, a solution that exploits the available depth map data, together with the multi-view geometry, is proposed to identify a better DE search area; such that it allows a reduction in its search points. It also exploits the number of different depth levels present within the current macro-block to determine which modes can be used for DE to further reduce its computations. Simulation results demonstrate that this can save up to 95% of the encoding time, with little influence on the coding efficiency of the texture and the depth map multi-view video coding. This makes 3D video coding more practical for any consumer devices, which tend to have limited computational power.peer-reviewe

3D high definition video coding on a GPU-based heterogeneous system

H.264/MVC is a standard for supporting the sensation of 3D, based on coding from 2 (stereo) to N views. H.264/MVC adopts many coding options inherited from single view H.264/AVC, and thus its complexity is even higher, mainly because the number of processing views is higher. In this manuscript, we aim at an efficient parallelization of the most computationally intensive video encoding module for stereo sequences. In particular, inter prediction and its collaborative execution on a heterogeneous platform. The proposal is based on an efficient dynamic load balancing algorithm and on breaking encoding dependencies. Experimental results demonstrate the proposed algorithm's ability to reduce the encoding time for different stereo high definition sequences. Speed-up values of up to 90× were obtained when compared with the reference encoder on the same platform. Moreover, the proposed algorithm also provides a more energy-efficient approach and hence requires less energy than the sequential reference algorith

Image-based rendering and synthesis

Multiview imaging (MVI) is currently the focus of some research as it has a wide range of applications and opens up research in other topics and applications, including virtual view synthesis for three-dimensional (3D) television (3DTV) and entertainment. However, a large amount of storage is needed by multiview systems and are difficult to construct. The concept behind allowing 3D scenes and objects to be visualized in a realistic way without full 3D model reconstruction is image-based rendering (IBR). Using images as the primary substrate, IBR has many potential applications including for video games, virtual travel and others. The technique creates new views of scenes which are reconstructed from a collection of densely sampled images or videos. The IBR concept has different classification such as knowing 3D models and the lighting conditions and be rendered using conventional graphic techniques. Another is lightfield or lumigraph rendering which depends on dense sampling with no or very little geometry for rendering without recovering the exact 3D-models.published_or_final_versio

Fast inter-mode decision in multi-view video plus depth coding

Motion and disparity estimations are employed in Multi-view Video Coding (MVC) to remove redundancies present between temporal and different viewpoint frames, respectively, in both the color and the depth multi-view videos. These constitute the major computational expensive tasks of the video encoder, as iterative search for the optimal mode and its appropriate compensation vectors is employed to reduce the Rate-Distortion Optimization (RDO) cost function. This paper proposes a solution to limit the number of modes that are tested for RDO to encode the inter-view predicted views. The decision is based on the encoded information obtained from the corresponding Macroblock in the Base view, identified accurately by using the multi-view geometry together with the depth data. Results show that this geometric technique manages to reduce about 70% of the estimation's computational time and can also be used with fast geometric estimations to reduce up to 95% of the original encoding time. These gains are obtained with little degradation on the multi-view video quality for both color and depth MVC.peer-reviewe

Fast multi-view video plus depth coding with hierarchical bi-prediction

This research work is partially funded by STEPS-Malta and partially by the EU–ESF 1.25.The Multi-view Video Coding (MVC) standard was developed for efficient encoding of multi-view videos. Part of it requires the calculation of both disparity and motion estimations using a bi-prediction structure. These estimations involve an exhaustive search for the optimal compensation vectors from multiple forward and backward reference frames which, while being very efficient in terms of compression, results in high computational costs. This paper proposes a solution that utilizes the multi-view geometry along with the available depth data, to calculate more accurate predictors for both motion and disparity estimations, and for both directions of the prediction structure. Simulation results demonstrate that this technique is reliable enough to allow a substantial reduction in the search areas in all the reference frames. This in turn results in a significant speed-up gain of 3.2 times with a negligible influence on the coding efficiency, while encoding both the color and the depth MVVs.peer-reviewe

Object-based coding for plenoptic videos

A new object-based coding system for a class of dynamic image-based representations called plenoptic videos (PVs) is proposed. PVs are simplified dynamic light fields, where the videos are taken at regularly spaced locations along line segments instead of a 2-D plane. In the proposed object-based approach, objects at different depth values are segmented to improve the rendering quality. By encoding PVs at the object level, desirable functionalities such as scalability of contents, error resilience, and interactivity with an individual image-based rendering (IBR) object can be achieved. Besides supporting the coding of texture and binary shape maps for IBR objects with arbitrary shapes, the proposed system also supports the coding of grayscale alpha maps as well as depth maps (geometry information) to respectively facilitate the matting and rendering of the IBR objects. Both temporal and spatial redundancies among the streams in the PV are exploited to improve the coding performance, while avoiding excessive complexity in selective decoding of PVs to support fast rendering speed. Advanced spatial/temporal prediction methods such as global disparity-compensated prediction, as well as direct prediction and its extensions are developed. The bit allocation and rate control scheme employing a new convex optimization-based approach are also introduced. Experimental results show that considerable improvements in coding performance are obtained for both synthetic and real scenes, while supporting the stated object-based functionalities. © 2006 IEEE.published_or_final_versio

A Novel High Efficiency Fractal Multiview Video Codec

Multiview video which is one of the main types of three-dimensional (3D) video signals, captured by a set of video cameras from various viewpoints, has attracted much interest recently. Data compression for multiview video has become a major issue. In this paper, a novel high efficiency fractal multiview video codec is proposed. Firstly, intraframe algorithm based on the H.264/AVC intraprediction modes and combining fractal and motion compensation (CFMC) algorithm in which range blocks are predicted by domain blocks in the previously decoded frame using translational motion with gray value transformation is proposed for compressing the anchor viewpoint video. Then temporal-spatial prediction structure and fast disparity estimation algorithm exploiting parallax distribution constraints are designed to compress the multiview video data. The proposed fractal multiview video codec can exploit temporal and spatial correlations adequately. Experimental results show that it can obtain about 0.36 dB increase in the decoding quality and 36.21% decrease in encoding bitrate compared with JMVC8.5, and the encoding time is saved by 95.71%. The rate-distortion comparisons with other multiview video coding methods also demonstrate the superiority of the proposed scheme

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