Paper
29 January 2007 Optimal reverse frame selection for stored video delivery under constrained resources
Author Affiliations +
Proceedings Volume 6508, Visual Communications and Image Processing 2007; 65082G (2007) https://doi.org/10.1117/12.704594
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
Abstract
In this paper, we present an optimal reverse frame selection (RFS) algorithm based on dynamic programming for delivering stored video under both bandwidth and buffer size constraints. Our objective is to find a feasible set of frames that can maximize the video's accumulated motion metrics without violating any constraint. We further extend RFS to solve the problem of video delivery over VBR channels where the channel bandwidth is both limited and time-varying. In particular, we first run RFS offline for several bandwidth samples, and the computation complexity is modest and scalable with the aids of frame size stuffing and non-optimal state elimination. During online streaming, we only need to retrieve the optimal frame selection path from the pre-generated offline results, and it can be applied to any VBR channels that can be modelled as piecewise CBR channels. Experimental results show the good performance of our proposed algorithm.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dayong Tao and Jianfei Cai "Optimal reverse frame selection for stored video delivery under constrained resources", Proc. SPIE 6508, Visual Communications and Image Processing 2007, 65082G (29 January 2007); https://doi.org/10.1117/12.704594
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Cited by 1 scholarly publication.
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KEYWORDS
Video

Computer programming

Algorithms

Classification systems

Computer engineering

Electronic imaging

Gallium nitride

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