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Interactive Content-aware Video Streaming System with Fine Granularity Scalability
Author(s) -
YungChi Chang,
ChihWei Hsu,
Wei-Min Chao,
LiangGee Chen
Publication year - 2006
Publication title -
the journal of vlsi signal processing systems for signal image and video technology
Language(s) - English
Resource type - Journals
eISSN - 1573-109X
pISSN - 0922-5773
DOI - 10.1007/s11265-006-7511-8
Subject(s) - computer science , encoder , scalability , granularity , mpeg 4 , coding (social sciences) , scalable video coding , real time computing , overhead (engineering) , encoding (memory) , artificial intelligence , operating system , mathematics , statistics
Video streaming with varying transmission bandwidth is becoming increasingly important. In this paper, an interactive video streaming system is proposed. Fine Granularity Scalability (FGS) is applied to be the streaming video format. The computational complexity of FGS coding is analyzed to explore an efficient FGS implementation. A new transmission model is proposed for the realization of a content-aware video streaming. At encoder side, the current MPEG-4 FGS coding flow is reordered such that the picture-level maximum can be acquired in advance and bit-plane data can be dynamically adapted. With these proposed hardware-oriented optimization approaches, a hardwired FGS block-level processing core is proposed to achieve a cost-effective solution to FGS implementation. The streaming server can adaptively decide quality-enhanced region by selective enhancement according to both object information from encoding side and user-defined region from receiver side. From the simulation results, it's demonstrated that the proposed approach can provide better quality in users' interest regions with no bit-rate or complexity overhead.

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