DISCOVERING SIMILAR SEGMENTS BY TIME-PARAMETERIZED TRAJECTORY CLUSTERING

摘要：

This paper is targeted at effectively discovery of moving objects common movement patterns The algorithms proposed in this paper consider highly tempo-spatial relevance of moving objects, measure spatial and temporal density of moving objects by spatial properties like Euclidean distance and movement direction, and temporal property, discovery dynamic evolution process of moving object clusters by time-based plane sweeping method. Experimental results demonstrate our algorithms correctly discover similar segments from real satellite tracking dataset of bar-headed geese migration.

关键词： Trajectory clustering Moving object Line segment clustering Plane sweeping

作者: LUO ZE YAN BAOPING

作者单位: Computer Network Information Center, Chinese Academy of Science

会议类型: 国际会议

会议名称: 3rd International Conference on Mechanical and Electrical Technology(ICMET2011) (2011第三届机械与电气技术国际会议)

会议地点: 大连

会议语种:英文

页码: 591-597

在线出版日期: 2011-08-26（万方平台首次上网日期，不代表论文的发表时间）