Moving target classification using SVM probability and post-filtering

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.