Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences
Joint Authors
Li, Hui
Wang, Chuanxu
Liu, Yun
Zhang, Shujun
Cui, Xuehong
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-25
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Pedestrian tracking is a critical problem in the field of computer vision.
Particle filters have been proven to be very useful in pedestrian tracking for nonlinear and non-Gaussian estimation problems.
However, pedestrian tracking in complex environment is still facing many problems due to changes of pedestrian postures and scale, moving background, mutual occlusion, and presence of pedestrian.
To surmount these difficulties, this paper presents tracking algorithm of multiple pedestrians based on particle filters in video sequences.
The algorithm acquires confidence value of the object and the background through extracting a priori knowledge thus to achieve multipedestrian detection; it adopts color and texture features into particle filter to get better observation results and then automatically adjusts weight value of each feature according to current tracking environment.
During the process of tracking, the algorithm processes severe occlusion condition to prevent drift and loss phenomena caused by object occlusion and associates detection results with particle state to propose discriminated method for object disappearance and emergence thus to achieve robust tracking of multiple pedestrians.
Experimental verification and analysis in video sequences demonstrate that proposed algorithm improves the tracking performance and has better tracking results.
American Psychological Association (APA)
Li, Hui& Liu, Yun& Wang, Chuanxu& Zhang, Shujun& Cui, Xuehong. 2016. Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-17.
https://search.emarefa.net/detail/BIM-1099777
Modern Language Association (MLA)
Li, Hui…[et al.]. Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-17.
https://search.emarefa.net/detail/BIM-1099777
American Medical Association (AMA)
Li, Hui& Liu, Yun& Wang, Chuanxu& Zhang, Shujun& Cui, Xuehong. Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-17.
https://search.emarefa.net/detail/BIM-1099777
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099777