Bandwidth-efficient video file synchronization between remote clients is an important task. When heterogeneous mobile clients want to synchronize their local video data to that of a remote party at a desired resolution and distortion level, it is wasteful and unnecessary to retransmit the entire video data, especially when the differences are minor while the clients are limited in transmission bandwidth. We present VSYNC (video-sync), an incremental video file synchronization protocol that automatically detects and transmits differences between the video files without prior knowledge of what is different. VSYNC generalizes the popular universal file synchronization tool rsync to a semantics-aware utility that handles synchronization of video data. An important attribute of VSYNC is that it allows synchronization to within some quantitative distortion constraint. VSYNC can be easily embedded in a codec or transcoder, and can be used to synchronize videos encoded with different parameters or stored in different, possibly proprietary, formats. A hierarchical hashing scheme is designed to compare the video content at the remote ends, while a lossy distributed video coding framework is used to realize compression gains in the update steps. Experimental results of three heterogeneous mobile clients synchronizing to an updated video file at the remote server validate the performance gains in rate-savings attained by VSYNC compared to directly sending the updated video files using H.26x or synchronizing using universal file synchronization protocols such as rsync.
We consider the problem of communicating compact descriptors for the purpose of establishing visual correspondences
between two cameras operating under rate constraints. Establishing visual correspondences is a critical
step before other tasks such as camera calibration or object recognition can be performed in a network of cameras.
We verify that descriptors of regions which are in correspondence are highly correlated, and propose the use
of distributed source coding to reduce the bandwidth needed for transmitting descriptors required to establish
correspondence. Our experiments demonstrate that the proposed scheme is able to provide compression gains of
57% with minimal loss in the number of correctly established correspondences compared to a scheme that communicates
the entire image of the scene losslessly in compressed form. Over a wide range of rates, the proposed
scheme also provides superior performance when compared to simply transmitting all the feature descriptors.
We propose a novel method of exploiting inter-view correlation among cameras that have overlapping views in order to deliver error-resilient video in a distributed multi-camera system. The main focus in this work is on robustness which is imminently needed in a wireless setting. Our system has low encoding complexity, is robust while satisfying tight latency constraints, and requires no inter-sensor communication. In this work, we build on and generalize PRISM [Puri2002], an earlier proposed single-camera distributed video compression system. Specifically, decoder motion search, a key attribute of single-camera PRISM, is extended to the multi-view setting to include decoder disparity search based on two-view camera geometry. Our proposed system, dubbed PRISM-MC (PRISM multi-camera), achieved PSNR gains of up to 1.7 dB over a PRISM based simulcast solution in experiments over a wireless channel simulator.
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