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
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;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761397