NDLI: Boundary and shadow position-based moving objects detection

Content Provider	IEEE Xplore Digital Library
Author	Chunsheng Guo Jian Yu
Copyright Year	2012
Description	Author affiliation: College of Communication Engineering, Hangzhou Dianzi University, China(310018) (Chunsheng Guo; Jian Yu)
Abstract	Video moving objects detection has been an important task in video surveillance. As a single detection algorithm often results in detection error, especially when the characteristic of the object is similar with the background. In this paper, a new detection method based on boundary and shadow position is proposed to accurately detect object. Firstly, the pre-detection objects are extracted by using Sequential Kernel Density Approximation (SKDA) and RGB color space respectively. Then two boundary sets can be obtained by applying Sobel edge operator to the pre-detected objects, and the inconsistent boundary will be identified afterwards. For each inconsistent boundary pair, its associated curvature and shadow mark vector is used as criteria to evaluate the most probable location of the true boundary. The final object is extracted by choosing the merged pre-detection objects in region surrounded by the evaluated boundary. Experimental results show that the proposed algorithm performs better under different scenes compared with other existing algorithms.
Starting Page	86
Ending Page	89
File Size	304817
Page Count	4
File Format	PDF
ISBN	9781467309653
e-ISBN	9781467309646
DOI	10.1109/CISP.2012.6469714
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation models Image color analysis Moving objects detection Lighting Vectors Real-time systems Robustness Shadow mark vector Approximation methods Curvature
Content Type	Text
Resource Type	Article

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