Mean Shift Track Initiation Algorithm Based on Hough Transform

摘要：

To solve the problem of initiating tracks for multi-target in dense clutters environment, a Mean shift track initiation algorithm based on Hough transform is proposed.In the algorithm, firstly, hough transform is applied to transform observation points from input space, referred to as feature space into curves in a special parameter space; then a Mean shift clustering algorithm is executed to cluster the items gained in the parameter space, and the problem of peak seeking is also solved adaptively. Furthermore, a fuzzy influential factor, which is based on the vote number of accumulation matrix and distance between items in the parameter space and clustering center, is defined to design kernel function of Mean shift; thus clutters are removed more effectively. Experimental results show that proposed algorithm has high detection accuracy and can initiate tracks effectively.

关键词： Track initiation Hough transform Mean Shift Clustering

作者: Lijun Zhou Weixin Xie Liangqun Li

作者单位: ATR Lab, Shenzhen University, Shenzhen , Guangdong, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1263-1266

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）