A Pedestrian Detection Method Based on MB_LBP Features and Intersection Kernel SVM

摘要：

　　Pedestrian detection is a hot research topic in pattern recognition and computer vision.We combine MB_LBP(Multiscale Block Local Binary Patterns)feature and Histogram Intersection Kernel SVM and apply them to pedestrian detection.MB_LBP features,which make up for the lack of LBP(Local Binary Patterns)features in robustness,is a kind of effective texture description operator.Histogram Intersection Kernel Support Vector Machine has the advantage of fast classification and high accuracy in object recognition.It can be used for further enhancing the systems real-time performance.The experiments show that the proposed approach has higher precision than the classical algorithm HOG+ LinearSVM and the HOG_LBP Features Fusion tested on the established benchmarking datasets-INRIA.

关键词： Pedestrian detection MB_LBP features HIKSVM

作者: Xuejie Nian Ke Xie Wankou Yang Changyin Sun

作者单位: School of Automation,Southeast University,Nanjing 210096,China;Key Lab of Measurement and Control of School of Automation,Southeast University,Nanjing 210096,China;Key Lab of Measurement and Control of

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 361-369

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）