DocumentCode :
625742
Title :
Alleviating cavity problems in moving object detection based on hysteresis thresholding and multi-models
Author :
Chin-Yang Lin ; Wei-Wen Chang ; Prangjarote, Panyaporn ; Chia-Hung Yeh ; Guo-Shiang Lin
fYear :
2013
fDate :
3-6 June 2013
Firstpage :
191
Lastpage :
192
Abstract :
Traditional background modeling methods often require complicated computations and suffer from cavity problems in foreground objects. In this paper, we propose a block-based background modeling method combining multiple detection results derived from color and texture characteristics. This method can significantly alleviate the cavity problem and resist certain shadow interference. Since the proposed scheme only requires low complexity, it is suitable for real-time applications.
Keywords :
Gaussian processes; image colour analysis; image texture; object detection; video surveillance; GMM; Gaussian mixture model; block-based background modeling method; cavity alleviation problems; color characteristics; hysteresis thresholding; moving object detection; multimodels; shadow interference; smart video surveillance system; texture characteristics; Adaptation models; Cavity resonators; Color; Colored noise; Computational modeling; Image color analysis; Real-time systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics (ISCE), 2013 IEEE 17th International Symposium on
Conference_Location :
Hsinchu
ISSN :
0747-668X
Print_ISBN :
978-1-4673-6198-9
Type :
conf
DOI :
10.1109/ISCE.2013.6570179
Filename :
6570179
Link To Document :
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