Abstract
Real-time multi-view video streaming plays an important role in new interactive and augmented video applications such as telepresence, remote surgery, and entertainment. Multiview video streaming approaches exploit time and inter-camera domain correlations in video frames for compression, thereby obtaining two benefits: video traffic reduction and video quality maintenance. However, excessive video encoding requires long periods of time for encoding/decoding computation in real-time multi-view video streaming and this process is vulnerable to frame loss, both of which may induce stalling and skipping during video playback at the user node. To address these problems, we propose Adaptive Multi-view Video Streaming (AMVS) system for real-time streaming. AMVS employs a greedy algorithm to adaptively select a prediction structure with low encoding/decoding computation based on the available network bandwidth. AMVS encodes and transmits multi-view video by considering the similarity of the user's request and the efficiency of transmission. Evaluations using Joint Multiview Video Coding (JMVC) demonstrated that AMVS achieves low encoding/decoding computation and high video quality while satisfying bandwidth limitations.
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