Sean Zhou and Shih - Ping
نویسندگان
چکیده
Over low bit rate channels, we adopt the streaming of nonlinearly sampled video frames (i.e., key-frame slideshow) synchronized with the audio stream. Given the channel and buffer limits, we wish to obtain a set of sampled frames that is not only feasible (i.e., no frame drop) but also optimal in terms of maximal information flow (given that the semantic information contents of each frame can be quantified in a way either automatically or manually). Different application scenarios are considered and modeled in a principle way, for which we propose computationally efficient algorithms for finding the global optimal solution. The algorithms are linear with respect to the total number of frames thus computationally efficient. The contributions of this paper include the novel modeling scheme for channel and buffer limits in the video temporal sampling problem; the development of the corresponding efficient algorithms for finding the global optimal solution; and the extension and analysis of these algorithms for practical application scenarios. The proposed algorithms have made possible the automated production of the new form of video streaming over low bit rate channels for devices with limited memory and storage capability. Index Termsvideo streaming, low bit rate communication, nonlinear temporal sampling, dynamic programming, Z-B diagram, T-C knapsack problem.
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Over low bit rate channels, we adopt the streaming of nonlinearly sampled video frames (i.e., key-frame slideshow) synchronized with the audio stream. Given the channel and buffer limits, we wish to obtain a set of sampled frames that is not only feasible (i.e., no frame drop) but also optimal in terms of maximal information flow (given that the semantic information contents of each frame can ...
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