关键词:支持向量机; 后验概率; 均值滤波; 运动目标分类
Moving target classification using SVM probability and post-filtering
LI Zhan-chuang, XIAO Guo-qiang, DAI Yi, QIU Kai-jin
(College of Computer & Information Science, Southwest University, Chongqing 400715, China)
Abstract:This paper presented a new method to classify moving targets, in which the outputs of standard SVMs could be mapped directly into target category’s posterior probabilities by the sigmoid function. Furthermore,also put forward a post-filtering framework to improve classification accuracy, using a weighted average filter to smooth the initial outputs of SVM classifiers. Experimental results demonstrate that the framework of SVM probability outputs combined with a post-filter is more effective for moving target classification from video in terms of classification accuracy.
Key words:SVM(support vector machine); posterior probability; average-filtering; moving target classification ......