Fast Moving- Object Detection in H.264/AVC Compressed Domain for Video Surveillance

被引:0
|
作者
Tom, Manu [1 ]
Babu, R. Venkatesh [1 ]
机构
[1] Indian Inst Sci, SERC, Video Analyt Lab, Bangalore 560012, Karnataka, India
关键词
Motion Segmentation; Compressed Domain; H.264/AVC; Video Surveillance; QP-delta; SEGMENTATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper discusses a novel fast approach for moving object detection in H.264/AVC compressed domain for video surveillance applications. The proposed algorithm initially segments out edges from regions with motion at macroblock level by utilizing the gradient of quantization parameter over 2D-image space. A spatial median filtering of the segmented edges followed by weighted temporal accumulation accounts for whole object segmentation. To attain sub-macroblock (4 x 4) level precision, the size of macroblocks (in bits) is interpolated using a two tap filter. Partial decoding rules out the complexity involved in full decoding and gives fast foreground segmentation results. Compared to other compressed domain techniques, the proposed approach allows the video streams to be encoded with different quantization parameters across macroblocks thereby increasing flexibility in bit rate adjustment.
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页数:4
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