Convex Optimization Based Bit Allocation for Light Field Compression under Weighting and Consistency Constraints

Compared with conventional image and video, light field images introduce the weight channel, as well as the visual consistency of rendered view, information that has to be taken into account when compressing the pseudo-temporal-sequence (PTS) created from light field images. In this paper, we propose a novel frame level bit allocation framework for PTS coding. A joint model that measures weighted distortion and visual consistency, combined with an iterative encoding system, yields the optimal bit allocation for each frame by solving a convex optimization problem. Experimental results show that the proposed framework is effective in producing desired distortion distribution based on weights, and achieves up to 24.7% BD-rate reduction comparing to the default rate control algorithm.Comment: published in IEEE Data Compression Conference, 201

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Low-latency compression of mocap data using learned spatial decorrelation transform

Due to the growing needs of human motion capture (mocap) in movie, video games, sports, etc., it is highly desired to compress mocap data for efficient storage and transmission. This paper presents two efficient frameworks for compressing human mocap data with low latency. The first framework processes the data in a frame-by-frame manner so that it is ideal for mocap data streaming and time critical applications. The second one is clip-based and provides a flexible tradeoff between latency and compression performance. Since mocap data exhibits some unique spatial characteristics, we propose a very effective transform, namely learned orthogonal transform (LOT), for reducing the spatial redundancy. The LOT problem is formulated as minimizing square error regularized by orthogonality and sparsity and solved via alternating iteration. We also adopt a predictive coding and temporal DCT for temporal decorrelation in the frame- and clip-based frameworks, respectively. Experimental results show that the proposed frameworks can produce higher compression performance at lower computational cost and latency than the state-of-the-art methods.Comment: 15 pages, 9 figure

Quality of Experience and Adaptation Techniques for Multimedia Communications

The widespread use of multimedia services on the World Wide Web and the advances in end-user portable devices have recently increased the user demands for better quality. Moreover, providing these services seamlessly and ubiquitously on wireless networks and with user mobility poses hard challenges. To meet these challenges and fulfill the end-user requirements, suitable strategies need to be adopted at both application level and network level. At the application level rate and quality have to be adapted to time-varying bandwidth limitations, whereas on the network side a mechanism for efficient use of the network resources has to be implemented, to provide a better end-user Quality of Experience (QoE) through better Quality of Service (QoS). The work in this thesis addresses these issues by first investigating multi-stream rate adaptation techniques for Scalable Video Coding (SVC) applications aimed at a fair provision of QoE to end-users. Rate Distortion (R-D) models for real-time and non real-time video streaming have been proposed and a rate adaptation technique is also developed to minimize with fairness the distortion of multiple videos with difference complexities. To provide resiliency against errors, the effect of Unequal Error protection (UXP) based on Reed Solomon (RS) encoding with erasure correction has been also included in the proposed R-D modelling. Moreover, to improve the support of QoE at the network level for multimedia applications sensitive to delays, jitters and packet drops, a technique to prioritise different traffic flows using specific QoS classes within an intermediate DiffServ network integrated with a WiMAX access system is investigated. Simulations were performed to test the network under different congestion scenarios