Visual Tracking Based on Incremental Two-Dimensional Mazimum Margin Criterion

摘要：

This paper presents a novel visual tracking algo-rithm based on incremental two-dimensional Maximum Margin Criterion (2DMMC). 2DMMC is a promising discriminant criterion for image feature extraction and its specialities make it a good choice for visual tracking problem. The proposed approach uses the 2DMMC to learn a discriminant projection matrix that best separates the target from the background. The projection matrix is updated online by a incremental algorithm to handle the appearance variations of the target and background. A particle filter using an efficient likelihood function based on the projection matrix is used to predict the target location in each frame. Experiments show that the proposed tracking algorithm is able to track the target in complex scenarios.

关键词： Visual Tracking Incremental Subspace Learn-ing Mazimum Margin Criterion

作者: Lu Wang

作者单位: School of Computer Engineering and Science Shanghai University Shanghai,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2684-2687

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）