Real-time foreground-background segmentation using adaptive support vector machine algorithm

Authors:
Zhifeng Hao;Wen Wen;Zhou Liu;Xiaowei Yang
Affiliations:
School of Mathematical Science, South China University of Technology, Guangzhou, China;College of Computer Science and Engineering, South China University of Technology, Guangzhou, China;National Lab of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;School of Mathematical Science, South China University of Technology, Guangzhou, China
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

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Abstract

In this paper, a SVM regression based method is proposed for background estimation and foreground detection. Incoming frames are treated as time series and a fixed-scale working-set selecting strategy is specifically designed for real-time background estimation. Experiments on two representative videos demonstrate the application potential of the proposed algorithm and also reveal some problems underlying it. Both the positive and negative reports from our study offer some useful information for researchers both in the field of image processing and that of machine learning.