A Vehicle Trajectory Analysis Approach Based on the Rigid Constraints of Object in 3-D Space

被引:0
作者
Wen Jiang [1 ]
Zhang Zhaoyang [1 ]
Song Huansheng [1 ]
Pang Fenglan [1 ]
机构
[1] Changan Univ, Sch Informat Engn, Xian 710064, Shaanxi, Peoples R China
来源
PATTERN RECOGNITION (CCPR 2016), PT I | 2016年 / 662卷
基金
中国国家自然科学基金;
关键词
Trajectory clustering; Rigid constraints; Camera calibration; 3-D reconstruction; SURVEILLANCE;
D O I
10.1007/978-981-10-3002-4_4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A reliable and effective trajectories similarity metric is one of key factors for vehicle trajectories clustering problem. A trajectory clustering algorithm based on the rigid constraints of vehicles in 3-D space is proposed in this paper, which conducts vehicle trajectories clustering effectively and precisely by using a new 3-D trajectories similarity metric. Based on two key procedures, camera calibration and a reconstruction of 2-D trajectories in 3-D space, a valuable principle that the heights of the trajectories have a linear relationship between them is found through using the kinematic properties of vehicle rigid body in moving. A more valuable information need to be pay attention is that the height of two trajectories that with displacement difference satisfies a plane surface character in 3-D space when conducts a height enumeration. The experimental results show that the trajectories are very stable and reliable for clustering and event detection when reconstructing their relative position in 3-D world coordinate system.
引用
收藏
页码:42 / 52
页数:11
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