Robust Tracking with Spatial Pyramid Histogram

摘要：

This paper presents a new method for object tracking based on global spatial correspondence with the geometric distribution of visual words.“Spatial Pyramid Histogram – SPH is produced by partitioning the image into increasing sub-blocks and computing histograms of features found inside each sub-block.SIFT descriptors are extracted to represent the object to construct a visual dictionary.A classifier is applied to discriminate the target from a number of candidates generated by randomly sampling.Our method also provides a solution to update the dictionary and the spatial information of visual words through selecting most distinctive samples to retrain the classifier.The experiments demonstrate that our method can track objects accurately and robustly even with scaling,rotation,especially partial or severe occlusion.

关键词： Spatial Pyramid Histogram Bag of Words Visual Tracking Robust Tracking

作者: Dong Wang Xiaohui Li Gang Yang Huchuan Lu

作者单位: School of Information and Communication Engineering, Dalian University of Technology, Dalian,116024, School of Information Science and Engineering, Northeastern University, Shenyang,110819,China School of Information and Communication Engineering,Dalian University of Technology,Dalian,116024,Ch

会议类型: 国际会议

会议名称: 第三届全国智能视觉监控学术会议

会议地点: 北京

会议语种:英文

页码: 9-12

在线出版日期: 2011-12-01（万方平台首次上网日期，不代表论文的发表时间）