Robust Vehicle Tracking based on Scale Invariant Feature Transform

摘要：

Vehicle tracking is a challenging problem in Intel- ligent Transport System.This paper presents a vehicle tracking approach combining blob based tracking and feature based tracking.First objects are detected as blobs using codebook(CB) algorithm and Scale Invariant Feature Transform(SIFT)features are extracted from the blobs.Then vehicles are tracked using SIFT to match the vehicles frame-by-frame.The method is robust to partial occlusion,partial af .ne distortion,changing in illumination,shape and size of vehicle.The experiments show that it is effective for vehicle tracking.

作者: Qiu Tu Yiping Xu Manli Zhou

作者单位: Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan,Hubei Province,China

会议类型: 国际会议

会议名称: 2008 IEEE International Conference on Onformation and Automation(IEEE 信息与自动化国际会议)

会议地点: 张家界

会议语种:英文

页码: 86-90

在线出版日期: 2008-06-20（万方平台首次上网日期，不代表论文的发表时间）