计算机工程2012，Vol.38Issue(17)：157-161,5.DOI:10.3969/j.issn.1000-3428.2012.17.044
基于改进Hausdorff距离的轨迹聚类算法
Trajectory Clustering Algorithm Based on Improved Hausdorff Distance
摘要
Abstract
For problems which the whole trajectory as the target for the clustering, this paper proposes a clustering algorithm called CTIHD(Clustering of Trajectories based on Improved Hausdorff Distance), which uses a sub- trajectory as the target for the clustering. In this algorithm, in order to effectively calculate the similarity between the trajectory, the algorithm defines a new sub-trajectory distance metrics, the definition can not only effectively eliminate the public error between sub-trajectory, but also take full account of sub-trajectory contains the movement feature. In algorithm, trajectory is divided into sub-trajectories uses the concept of the trajectory of feature point. It uses the proposed the definition of trajectory distance metrics between sub-trajectories to calculated similarity between sub-trajectories; On this basis, the use of traditional clustering methods for sub-trajectory clustering. Experimental results show that the algorithm can achieve better trajectory clustering effect than the existing methods.关键词
轨迹聚类/运动模式/Hausdorff距离/点特征矩阵/轨迹子段Key words
trajectory clustering/ movement pattern/ Hausdorff Distance(HD)/ point characteristic matrix/ sub-trajectory分类
信息技术与安全科学引用本文复制引用
陈锦阳,宋加涛,刘良旭,王让定..基于改进Hausdorff距离的轨迹聚类算法[J].计算机工程,2012,38(17):157-161,5.基金项目
国家自然科学基金资助项目(60972163) （60972163）
浙江省自然科学基金资助项目(Y1100598) （Y1100598）
信息处理与自动化技术浙江省重中之重学科开放基金资助项目(201100808) （201100808）
浙江省综合信息网技术重点实验室开放基金资助项目(201109) （201109）
宁波市自然科学基金资助项目(2009A610090,2011A610175) （2009A610090,2011A610175）
