DocumentCode
2481241
Title
Complex background modeling and motion detection based on Texture Pattern Flow
Author
Zhang, Baochang ; Gao, Yongsheng ; Zhong, Bineng
Author_Institution
Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
This paper proposes a novel texture pattern flow (TPF) for complex background modeling and motion detection. The pattern flow is proposed to encode the binary pattern changes among the neighborhoods in the space-time domain. To model the distribution of the TPF, the TPF integral histograms are used to extract the discriminative features to represent the input video. Experimental results on the public videos testify the effectiveness of the proposed method in comparison to LBP and GMM based background modeling methods.
Keywords
feature extraction; image coding; image representation; image texture; motion estimation; object detection; statistical distributions; video signal processing; TPF integral histogram; binary pattern change encoding; complex background modeling; feature extraction; object motion detection; space-time domain; statistical distribution; texture pattern flow; video representation; Automation; Educational institutions; Feature extraction; Histograms; Image sequences; Intelligent systems; Layout; Motion detection; Space technology; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761397
Filename
4761397
Link To Document