Adaptive streaming of multi-view video over P2P networks

In this paper, we propose a novel solution for the adaptive streaming of 3D representations in the form of multi-view video by utilizing P2 Poverlay networks to assist the media delivery and minimize the bandwidth requirement at the server side. Adaptation to diverse network conditions is performed regarding the features of human perception to maximize the perceived 3D. We have performed subjective tests to characterize these features and determined the best adaptation method to achieve the highest possible perceived quality. Moreover, we provide a novel method for mapping from scalable video elementary stream to torrent-liked at a chunks for adaptive video streaming and provide an optimized windowing mechanism that ensures timely delivery of the content over yanlıs gibi. The paper also describes techniques generating scalable video chunks and methods for determining system parameters such as chunksize and window length.