High-dimensional statistical distance for object tracking

摘要：

This paper deals with object tracking in the video sequences. The goal is to determine in successive frames the object which best matches. So we used the similar measure between the reference object and candidate object can be distinguished: Relying on the same principle of histogram distance, but within a probabilistic framework, we introduce a new tracking technique. First, measure based solely radiometry include distances between probability density function of color histograms. Then we propose to compute the Chebyshev distance between high-dimensional PDF without explicitly estimating the PDF. The distance is expressed directly from the sample using the nearest neighbor framework. It capability of the tracker to target object variations, is demonstrated for several image sequences.

关键词： Similarity Measures Nearest Neighbor Tracking Chebyshev Distance Histogram Estimator

作者: Zhang Yang Ye Shufan Xiang Yang Gao Liqun

作者单位: College of Information Science and Engineering, Northeastern University, Shenyang 110004 College of Resource and Civil Engineering, Northeastern University, Shenyang 110004

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 1511-1514

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）