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Behavior pattern extraction by trajectory analysis |
Jia WEN1,2( ), Chao LI1, Zhang XIONG1 |
1. School of Computer Science and Engineering, Beihang University, Beijing 100191, China; 2. Department of Computer, College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China |
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Abstract Trajectory clustering and behavior pattern extraction are the foundations of research into activity perception of objects in motion. In this paper, a new framework is proposed to extract behavior patterns through trajectory analysis. Firstly, we introduce directional trimmed mean distance (DTMD), a novel method used to measure similarity between trajectories. DTMD has the attributes of anti-noise, self-adaptation and the capability to determine the direction for each trajectory. Secondly, we use a hierarchical clustering algorithm to cluster trajectories. We design a length-weighted linkage rule to enhance the accuracy of trajectory clustering and reduce problems associated with incomplete trajectories. Thirdly, the motion model parameters are estimated for each trajectory’s classification, and behavior patterns for trajectories are extracted. Finally, the difference between normal and abnormal behaviors can be distinguished.
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Keywords
trajectory clustering
directional trimmed mean distance (DTMD)
behavior pattern extraction
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Corresponding Author(s):
WEN Jia,Email:wjyanyuan@yahoo.com.cn
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Issue Date: 05 March 2011
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