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Online smoothness with dropping partial data based on advanced video coding stream

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Abstract

Most studies of smoothing video stream compute the required bit rate of video transmission to satisfy all the transmitted data. In this paper, our proposed online smoothing with tolerable data dropping algorithm can adjust the bit rate as smooth as possible. Several multimedia encoding schemes, such as advanced video coding (AVC), can support partial data dropping to adapt to available bandwidth network. The AVC stream can be adapted by smoothing algorithm to ensure video quality for a given set of constraints where these constraints may be either static after the session set up or may dynamically change over the session duration. Our algorithm is based on the online minimum variance bandwidth allocation algorithm to look ahead a window of frames, dynamically adjusting the required bit rate such that ensuring smoothness when the buffer encounters underflow or overflow for video stream. Furthermore, we add the scheme of data dropping into this algorithm to increase the possibility of smoothing bit rates. The experimental results show the peak rate, the average ratio of dropped data, and the coefficient of variation for five test sequences with different content characteristics such as the average frame size, the peak/mean ratio of frame size, and the average frame bit rate. Experimental parameters are varied by window sizes and tolerable dropping ratios. The algorithm can significantly reduce the peak rate and the coefficient of variation when the transmitted packets are allowed dropping by a user-defined dropping ratio.

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Acknowledgements

This work was supported by Chang Jung Christian University under Contract Q1000005.

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Correspondence to Huey-Min Sun.

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Sun, HM. Online smoothness with dropping partial data based on advanced video coding stream. Multimed Tools Appl 69, 1021–1040 (2014). https://doi.org/10.1007/s11042-012-1141-x

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