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Title: Fast and robust object-extraction framework for object-based streaming system

Authors: Ashraf M.A. Ahmad, Suh-Yin Lee

Addresses: Department of Computer Science and Information Engineering, National Chiao-Tung University, 1001 Ta-Hsueh Rd, Hsinchu, Taiwan. ' Department of Computer Science and Information Engineering, National Chiao-Tung University, 1001 Ta-Hsueh Rd, Hsinchu, Taiwan

Abstract: Video streaming poses significant technical challenges in the quality of service guarantee and efficient resource management. In this paper, we propose an efficient moving object-extraction algorithm suitable for real-time content-based multimedia streaming systems. A motion vector based object extraction is used to dynamically detect the objects. To utilise the bandwidth efficiently, the video objects can be detected in real time, encoded, and transmitted with higher quality and a higher frame rate than those in the background. To meet the real-time requirement, no computationally intensive operation is included in this framework. Moreover, to guarantee the highest speed, the entire implementation is operating in the compressed domain without any need for decompression.

Keywords: object extraction; video streaming; MPEG1; MPEG2; texture; motion vector; quality of service; resource management; QoS; real-time content; multimedia streaming.

DOI: 10.1504/IJVTM.2008.017109

International Journal of Virtual Technology and Multimedia, 2008 Vol.1 No.1, pp.39 - 60

Published online: 13 Feb 2008 *

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