Human Detection Base On Pc-SVM

摘要：

PC-SVM is a new developed support vector machine classifier with probabilistic constrains which presence of samples probability in each class is determined based on a distribution function. The presence of noise causes incorrect calculation of support vectors thereupon margin can not be maximized. In the Pc-SVM, constraints boundaries and constraints occurrence have probability density functions which it helps for achieving maximum margin. The main target of this paper is introducing a robust visual object recognition based on PC-SVM. Human detection is used as benchmark problem for the proposed algorithm. Experimental results show superiority of the probabilistic constraints support vector machine (PC-SVM) relative to standard SVM in human detection.

关键词： pc-svm human detection histograms of oriented gradients

作者: Seyyed Meysam Hosseini Abbas Nasrabadi

作者单位: Electrical Engineering Group Azad University of Firoozkuh Firoozkuh,Iran Electrical Engineering Department Tarbiat Moallem University of Sabzevar Sabzevar, Iran

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Computer Science and Information Technology(第三届IEEE计算机科学与信息技术国际会议 ICCSIT 2010)

会议地点: 成都

会议语种:英文

页码: 141-144

在线出版日期: 2010-07-07（万方平台首次上网日期，不代表论文的发表时间）