DocumentCode
502972
Title
Moving object detection algorithm for H.264/AVC compressed video stream
Author
Qiya, Zhou ; Zhicheng, Liu
Author_Institution
Dept. of Inf. Technol., Hunan Railway Coll. of Sci. & Technol., Zhuzhou, China
Volume
1
fYear
2009
fDate
8-9 Aug. 2009
Firstpage
186
Lastpage
189
Abstract
Moving object segmentation directly from compressed video stream is a challenging task in video signal processing community. A novel moving object detection algorithm for H.264/AVC stream is presented in this paper. Firstly, a series of operations, including spatial-temporal normalization, bidirectional accumulation, median filtering and thresholding magnitudes, are conducted on the raw motion vector (MV) field so as to gain a robust MV field, which can indicate the moving region reliably. Then global motion compensation in compressed domain is implemented if there exist global motion caused by camera. Finally, the macroblock coded mode with variable size is combined with the temporal information to locate the foreground object. Its effectiveness of the proposed algorithm has been demonstrated in our experimental results. The main advantage of the algorithm lies in its robustness and real-time performance.
Keywords
image segmentation; median filters; motion compensation; object detection; video coding; video streaming; H.264/AVC; bidirectional accumulation; compressed video stream; global motion compensation; macroblock coded mode; median filtering; motion vector field; moving object detection; moving object segmentation; spatial-temporal normalization; video signal processing; Automatic voltage control; Filtering; Motion compensation; Object detection; Object segmentation; Robustness; Signal processing algorithms; Streaming media; Video compression; Video signal processing; H.264/AVC; compressed domain; moving object detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location
Sanya
Print_ISBN
978-1-4244-4247-8
Type
conf
DOI
10.1109/CCCM.2009.5270474
Filename
5270474
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