Online Unsupervised Learning Classification of Pedestrian and Vehicle for Video Surveillance  

作　　者：HE Yi SANG Nong GAO Changxin HAN Jun 

机构地区：[1]School of Automation,Huazhong University of Science and Technology,Wuhan 430074,China [2]Air Force Early Warning Academy,Wuhan 430019,China

出　　处：《Chinese Journal of Electronics》2017年第1期145-151,共7页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.61371047);Research Fund for the Doctoral Program of Higher Education of China(No.20110185110014)

摘　　要：This paper presents an online unsupervised learning classification of pedestrians and vehicles for video surveillance. Different from traditional methods depending on offline training, our method adopts the online label strategy based on temporal and morphological features,which saves time and labor to a large extent. It extract the moving objects with their features from the original video.An online filtering procedure is adopted to label the moving objects according to certain threshold of speed and area feature. The labeled objects are sent into a SVM classifier to generate the pedestrian & vehicle classifier. Experimental results illustrate that our unsupervised learning algorithm is adapted to polymorphism of the pedestrians and diversity of the vehicles with high classification accuracy.This paper presents an online unsupervised learning classification of pedestrians and vehicles for video surveillance. Different from traditional methods depending on offline training, our method adopts the online label strategy based on temporal and morphological features,which saves time and labor to a large extent. It extract the moving objects with their features from the original video.An online filtering procedure is adopted to label the moving objects according to certain threshold of speed and area feature. The labeled objects are sent into a SVM classifier to generate the pedestrian ＆ vehicle classifier. Experimental results illustrate that our unsupervised learning algorithm is adapted to polymorphism of the pedestrians and diversity of the vehicles with high classification accuracy.

关 键 词：Online learning Unsupervised Objects classification Video surveillance 

分 类 号：TN948.6[电子电信—信号与信息处理]