Feature Selection Based On AdaBoost In Video Surveillance System

摘要：

At present, feature-based classification method is widely used in video surveillance system. How to find a group of features which are stable and efficient is concerned by researchers. In this paper, a new method based on AdaBoost is proposed to form a good sub-set of features. This method evaluates the performance of each feature, and then selects features from the extracted features for classification. Under the premise of ensuring the classification accuracy, the speed of the classifier is greatly improved.

关键词： feature selection AdaBoost object classification

作者: Bin Tian Xiaoshi Zheng Rangyong Zhang Yanling Zhao

作者单位: Shandong Institute Of Light Industry Shandong Computer Science Center Jinan,China Shandong Computer Science Center Jinan, China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 3049-3051

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）