A Robust Approach for Congested Vehicles Tracking Basd on Tracking-Model-Detection Framework

摘要：

　　Congested vehicles tracking is one of the most challenging problems in Intelligent Transportation System.Partial occlusions significantly undermine the performance of vehicles tracking in congested situation.Gradual occlusion often causes the drifting problem in many vehicles tracking methods.In this paper,we propose a robust algorithm for congested vehicles tracking based on Tracking-Modeling-Detection (TMD) framework system.We improve this method to track congested vehicles and apply it in traffic application.New rectangle region choosing strategy is proposed to select new tracking rectangle regions that contain best feature points when occlusion happens.Instead picking points on the rectangle grid in TMD method,we utilize points with good feature to enhance the efficiency and accuracy of tracking.The paper also presents experiment using video sequences of challenging congest traffic to verify the proposed method.

关键词： Intelligent Transportation System occlusion Tracking-Modeling-Detection congested vehicle tracking

作者: Dan Tu Jun Lei Yazhou Yang

作者单位: National University of Defense Technology Changsha Hunan 410073, China

会议类型: 国际会议

会议名称: 2012 IEEE 11th International Conference on Signal Processing (第11届IEEE信号处理国际会议)

会议地点: 北京

会议语种:英文

页码: 820-824

在线出版日期: 2012-10-21（万方平台首次上网日期，不代表论文的发表时间）