A SVM Kernel for Classifying Partially Occluded Images

摘要：

We propose a novel SVM (Support Vector Machine) kernel for classifying partially occluded images in the process of video tracking. The SVM kernel (called Bhattacharyya kernel) is derived from Bhattacharyya coefficient. In our study, the validity of Bhattacharyya kernel is proven. We use kernel density estimation of histogram as SVMs feature space. Experiments show the SVM based on Bhattacharyya kernel can keep high classification accuracy when occlusion or clutter of peripheral pixels appears. Bhattacharyya kernel can be generalized easily when using other features.

关键词： bhattacharyya kernel SVM kernel density estimation

作者: Risheng Han Hui Ding Guangxue Yue

作者单位: College of Mathematics and Information Engineering, Jiaxing University

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 615-618

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）