NDLI: Motion object detection method based on piecemeal principal component analysis of dynamic background updating

Content Provider	IEEE Xplore Digital Library
Author	Xiao-Jun Cao Bao-Chang Pan Sheng-Lin Zheng Chao-Yang Zhang
Copyright Year	2008
Description	Author affiliation: Inst. of Digital Image Technol., Guangdong Univ. of Technol., Guangzhou (Xiao-Jun Cao; Bao-Chang Pan; Sheng-Lin Zheng; Chao-Yang Zhang)
Abstract	On the traditional dynamic background updating method, homomorphic filter is used to reduce influence of illumination, and temporal difference is replaced by background subtraction in order to reduce area of motion object and the influence of illumination in the area of nearby motion object. Moreover, on this improving dynamic background updating method, this paper proposes a kind of motion object detection algorithm based on piecemeal principal component analysis. Differentiating from the traditional method whose principal component analysis is used to deal with the whole image, this method carries on piecemeal processing to the whole image, and then, principal component analysis is used to deal with each block of the image in order to give prominence to the principal characteristic. And the block of this principal characteristic contains motion object. So, we can detect the motion object easily. Experimental results prove that these methods offered above resolve the problem of illumination, and the accuracy is high. Also, the operation of this algorithm is not difficult.
Starting Page	2932
Ending Page	2937
File Size	321720
Page Count	6
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620910
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lighting Principal component analysis Dynamics Object detection Manganese Euclidean distance Cybernetics Object Detection Background Updating Principal Component Analysis
Content Type	Text
Resource Type	Article

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