Efficient content analysis engine for visual surveillance network
IEEE Transactions on Circuits and Systems for Video Technology
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Since motion-compensated temporal filtering (MCTF) becomes an important temporal prediction scheme in video coding algorithms, this paper presents an efficient temporal prediction engine which not only is the first MCTF hardware work but also supports traditional motion-compensated prediction (MCP) scheme to provide computation scalability. For the prediction stage of MCTF and MCP schemes, modified extended double current Frames is adopted to reduce the system memory bandwidth, and a frame-interleaved macroblock pipelining scheme is proposed to eliminate the induced data buffer overhead. In addition, the proposed update stage architecture with pipelined scheduling and motion estimation (ME)-like motion compensation (MC) with level C+ scheme can also save about half external memory bandwidth and eliminate irregular memory access for MC. Moreover, 76.4% hardware area of the update stage is saved by reusing the hardware resources of the prediction stage. This MCTF chip can process CIF 30 fps in real-time, and the searching range is [-32, 32) for 5/3 MCTF with four-decomposition level and also support 1/3 MCTF, hierarchical B-frames, and MCP coding schemes in JSVM and H.264/AVC. The gate count is 352-K gates with 16.8 KBytes internal memory, and the maximum operating frequency is 60 MHz.