NDLI: A pixel-wise local information-based background subtraction approach

Content Provider	IEEE Xplore Digital Library
Author	Zhong Wei Shuqiang Jiang Qingming Huang
Copyright Year	2008
Description	Author affiliation: Grad. Univ. of Chinese Acad. of Sci., Beijing (Zhong Wei)
Abstract	Background subtraction is a widely used method for moving object detection in computer vision. It is usually applied in video surveillance systems. There are two major kinds of background subtraction approaches: pixel-based and block based. Yet there are three problems that can not be simultaneously solved by either method: the robustness to illumination changes, the effectiveness in suppressing shadows, and the smoothness of foregroundpsilas boundary. In order to solve these problems, a pixel-wise local information-based background subtraction method is proposed in this paper. In the proposed method, Gabor filters are performed to extract the spatial feature vectors for each pixel from the source image sequence. Then, the spatial feature vectors are modeled by Gaussian Mixture Model, and then moving objects are detected. Experiments show the validity of the proposed method.
Starting Page	1501
Ending Page	1504
File Size	694954
Page Count	4
File Format	PDF
ISBN	9781424425709
DOI	10.1109/ICME.2008.4607731
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-23
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pixel Gabor filters Computational modeling Feature extraction Lighting Mathematical model Computer vision Gaussian Mixture Model Background subtraction spatial feature vector
Content Type	Text
Resource Type	Article

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