DocumentCode :
1665865
Title :
Robust compositional method for background subtraction
Author :
Xiaochun Liu ; Tao Zhong ; Dan Fu
Author_Institution :
Coll. of Aerosp. & Mater. Eng., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2012
Firstpage :
1419
Lastpage :
1424
Abstract :
We present a novel compositional method for background subtraction. The presented method can better handle multi-modal appearance of the background in a dynamic environment. In this method, an illumination compensation method based on Local Binary Pattern is used to compensate sudden global and/or local illumination changes, and it is also used for filtering the pixels from background rather than foreground for background subtraction algorithms. Using this scheme, we can improve the accuracy of background model and make our method better handle the high-frequency illumination changes. An efficient compositional scheme is proposed to combine the parameter-based and the samples-based algorithm for background subtraction. Thanks to this scheme, we can get more reliable results than any of them. A new initialization technique for Gaussian Mixture Model based on spatial information is also presented, which can help us get meaningful results from the second frame. Experimental results clearly justify our method.
Keywords :
Gaussian processes; computer vision; filtering theory; image sampling; Gaussian mixture model; background multimodal appearance; background subtraction; dynamic environment; high-frequency illumination change; illumination compensation method; initialization technique; local binary pattern; machine vision; parameter-based algorithm; pixel filtering; robust compositional method; samples-based algorithm; spatial information; sudden illumination change compensation; Accuracy; Adaptation models; Lighting; Noise; Robustness; Substations; Background Subtraction; Computational Method; Illumination Compensation; Local Binary Pattern; VIBE;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
Type :
conf
DOI :
10.1109/ICARCV.2012.6485397
Filename :
6485397
Link To Document :
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