Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7817
Title: An algorithm for video monitoring under a slow moving background
Authors: Zheng, JB
Feng, DD
Zhang, YN
Siu, WC 
Zhao, RC
Keywords: Affine transformation model
Background matching
Scene change detection
Slow moving background
Video monitoring
Issue Date: 2002
Source: Proceedings of 2002 International Conference on Machine Learning and Cybernetics, 2002, v. 3, p. 1626-1629 How to cite?
Abstract: In this paper, a video monitoring algorithm under a slow moving background is proposed. An affine transformation model is used to describe the background image movement and two methods are given to find the affine transformation model parameters. The affine transformation is used to check how well two frames can match and subsequently a subtraction operation based on block difference is performed for scene change detection. In order to finalize the detecting result, a series of image processing operations, including adaptive threshold, morphological dilation and erosion operation, and region labeling have to be performed. The several experiments are given to show that the proposed algorithm is efficient.
Description: Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, 4-5 November 2002
URI: http://hdl.handle.net/10397/7817
ISBN: 0-7803-7508-4
Appears in Collections:Conference Paper

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