Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition
Joint Authors
Zhao, Pengpeng
Wu, Jian
Cui, Zhiming
Sheng, Victor S.
Shi, Yujie
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-27
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target.
Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets.
Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering.
It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix.
Then, it clusters sample data points into different clusters.
After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed.
The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness.
The real-world application verified its feasibility and the validity.
American Psychological Association (APA)
Wu, Jian& Cui, Zhiming& Sheng, Victor S.& Shi, Yujie& Zhao, Pengpeng. 2014. Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1051254
Modern Language Association (MLA)
Wu, Jian…[et al.]. Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1051254
American Medical Association (AMA)
Wu, Jian& Cui, Zhiming& Sheng, Victor S.& Shi, Yujie& Zhao, Pengpeng. Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1051254
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051254