Rate-distortion optimization for stereoscopic video streaming with unequal error protection

We consider an error-resilient stereoscopic streaming system that uses an H.264-based multiview video codec and a rateless Raptor code for recovery from packet losses. One aim of the present work is to suggest a heuristic methodology for modeling the end-to-end rate-distortion (RD) characteristic of such a system. Another aim is to show how to make use of such a model to optimally select the parameters of the video codec and the Raptor code to minimize the overall distortion. Specifically, the proposed system models the RD curve of video encoder and performance of channel codec to jointly derive the optimal encoder bit rates and unequal error protection (UEP) rates specific to the layered stereoscopic video streaming. We define analytical RD curve modeling for each layer that includes the interdependency of these layers. A heuristic analytical model of the performance of Raptor codes is also defined. Furthermore, the distortion on the stereoscopic video quality caused by packet losses is estimated. Finally, analytical models and estimated single-packet loss distortions are used to minimize the end-to-end distortion and to obtain optimal encoder bit rates and UEP rates. The simulation results clearly demonstrate the significant quality gain against the nonoptimized schemes

3D video coding and transmission

The capture, transmission, and display of 3D content has gained a lot of attention in the last few years. 3D multimedia content is no longer con fined to cinema theatres but is being transmitted using stereoscopic video over satellite, shared on Blu-RayTMdisks, or sent over Internet technologies. Stereoscopic displays are needed at the receiving end and the viewer needs to wear special glasses to present the two versions of the video to the human vision system that then generates the 3D illusion. To be more e ffective and improve the immersive experience, more views are acquired from a larger number of cameras and presented on di fferent displays, such as autostereoscopic and light field displays. These multiple views, combined with depth data, also allow enhanced user experiences and new forms of interaction with the 3D content from virtual viewpoints. This type of audiovisual information is represented by a huge amount of data that needs to be compressed and transmitted over bandwidth-limited channels. Part of the COST Action IC1105 \3D Content Creation, Coding and Transmission over Future Media Networks" (3DConTourNet) focuses on this research challenge.peer-reviewe

PEER-TO-PEER 3D/MULTI-VIEW VIDEO STREAMING

Abstract The recent advances in stereoscopic video capture, compression and display have made 3D video a visually appealing and costly affordable technology. More sophisticated multi-view videos have also been demonstrated. Yet their remarkably increased data volume poses greater challenges to the conventional client/server systems. The stringent synchronization demands from different views further complicate the system design. In this thesis, we present an initial attempt toward efficient streaming of 3D videos over peer-to-peer networks. We show that the inherent multi-stream nature of 3D video makes playback synchronization more difficult. We address this by a 2-stream buffer, together with a novel segment scheduling. We further extend our system to support multi-view video with view diversity and dynamics. We have evaluated our system under different end-system and network configurations with typical stereo video streams. The simulation results demonstrate the superiority of our system in terms of scalability, streaming quality and dealing with view dynamics

Anahita: A System for 3D Video Streaming with Depth Customization

Producing high-quality stereoscopic 3D content requires significantly more effort than preparing regular video footage. In order to assure good depth perception and visual comfort, 3D videos need to be carefully adjusted to specific viewing conditions before they are shown to viewers. While most stereoscopic 3D content is designed for viewing in movie theaters, where viewing conditions do not vary significantly, adapting the same content for viewing on home TV-sets, desktop displays, laptops, and mobile devices requires additional adjustments. To address this challenge, we propose a new system for 3D video streaming that provides automatic depth adjustments as one of its key features. Our system takes into account both the content and the display type in order to customize 3D videos and maximize their perceived quality. We propose a novel method for depth adjustment that is well-suited for videos of field sports such as soccer, football, and tennis. Our method is computationally efficient and it does not introduce any visual artifacts. We have implemented our 3D streaming system and conducted two user studies, which show: (i) adapting stereoscopic 3D videos for different displays is beneficial, and (ii) our proposed system can achieve up to 35% improvement in the perceived quality of the stereoscopic 3D content

Subjective quality study of adaptive streaming of monoscopic and stereoscopic video

Nowadays, HTTP adaptive streaming (HAS) has become a reliable distribution technology offering significant advantages in terms of both user perceived Quality of Experience (QoE) and resource utilization for content and network service providers. By trading-off the video quality, HAS is able to adapt to the available bandwidth and display requirements so that it can deliver the video content to a variety of devices over the Internet. However, until now there is not enough knowledge of how the adaptation techniques affect the end user's visual experience. Therefore, this paper presents a comparative analysis of different bitrate adaptation strategies in adaptive streaming of monoscopic and stereoscopic video. This has been done through a subjective experiment of testing the end-user response to the video quality variations, considering the visual comfort issue. The experimental outcomes have made a good insight into the factors that can influence on the QoE of different adaptation strategies