Adapting the streaming video based on the estimated motion position

In real time video streaming, the frames must meet their timing constraints, typically specified as their deadlines. Wireless networks may suffer from bandwidth limitations. To reduce the data transmission over the wireless networks, we propose an adaption technique in the server side by extracting a part of the video frames that considered as a Region Of Interest (ROI), and drop the part outside the ROI from the frames that are between reference frames. The estimated position of the selection of the ROI is computed by using the Sum of Squared Differences (SSD) between consecutive frames. The reconstruction mechanism to the region outside the ROI is implemented in the mobile side by using linear interpolation between reference frames. We evaluate the proposed approach by using Mean Opinion Score (MOS) measurements. MOS are used to evaluate two scenarios with equivalent encoding size, where the users observe the first scenario with low bit rate for the original videos, while for the second scenario the users observe our proposed approach with high bit rate. The results show that our technique significantly reduces the amounts of data are streamed over wireless networks, while the reconstruction mechanism will provides acceptable video quality

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

Streaming and User Behaviour in Omnidirectional Videos

Omnidirectional videos (ODVs) have gone beyond the passive paradigm of traditional video, offering higher degrees of immersion and interaction. The revolutionary novelty of this technology is the possibility for users to interact with the surrounding environment, and to feel a sense of engagement and presence in a virtual space. Users are clearly the main driving force of immersive applications and consequentially the services need to be properly tailored to them. In this context, this chapter highlights the importance of the new role of users in ODV streaming applications, and thus the need for understanding their behaviour while navigating within ODVs. A comprehensive overview of the research efforts aimed at advancing ODV streaming systems is also presented. In particular, the state-of-the-art solutions under examination in this chapter are distinguished in terms of system-centric and user-centric streaming approaches: the former approach comes from a quite straightforward extension of well-established solutions for the 2D video pipeline while the latter one takes the benefit of understanding users’ behaviour and enable more personalised ODV streaming