NDLI: An updating algorithm of self-adaptive background based on energy method

Content Provider	IEEE Xplore Digital Library
Author	Zhenhua Wei Jun Tian Changan Liu Siyuan Wu
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Technol., North China Electr. Power Univ., Beijing (Zhenhua Wei; Jun Tian; Changan Liu; Siyuan Wu)
Abstract	With the large computation quantity, long computing time and low real-time performance, the optical flow is not fit for the complex surroundings. The background image difference is only fit for the still background and so far, no reasonable approach has been designed and implemented for automatic background updating along with the background variance. To solve the above problems, an updating algorithm of self-adaptive background based on energy method (USBE) first is proposed in this paper. In the complicated background, this algorithm is mainly applied to the moving object detection, which can modify and update the coarse background model (CBM) in real time. Moreover, combining the background image difference and energy similarity of moving objects, this algorithm can extract the moving objects completely and its application is universal. Experimental results demonstrate that the proposed updating algorithm of self-adaptive background based on energy method (USBE) can update the variational background exactly and quickly and improve the recognition accuracy of the moving objects.
Starting Page	848
Ending Page	852
File Size	298909
Page Count	5
File Format	PDF
ISBN	9781424425020
DOI	10.1109/ICAL.2008.4636268
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems energy method Image segmentation Computer vision Computational modeling Noise background image difference moving object detection Image sequences Pixel coarse background model
Content Type	Text
Resource Type	Article

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