Real-Time Pedestrian Tracking and Counting with TLD

This paper describes a solution to solve the issue of automatic multipedestrian tracking and counting. First, background modeling algorithm is applied to actively obtain multipedestrian candidates, followed by a confirmation step with classification. Then each pedestrian patch is handled by real-tim...

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Bibliographic Details
Main Authors: Jiawei Shi, Xianmei Wang, Huer Xiao
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2018/8486906
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Summary:This paper describes a solution to solve the issue of automatic multipedestrian tracking and counting. First, background modeling algorithm is applied to actively obtain multipedestrian candidates, followed by a confirmation step with classification. Then each pedestrian patch is handled by real-time TLD (Tracking-Learning-Detection) to get a new predication position according to similarity measure. Further TLD results are compared with classification list to determine a new, disappeared, or existing pedestrian. Finally single line counting with buffer zone is employed to count pedestrians. Experiments results on the public database, PETS, demonstrate the validity of our solution.
ISSN:0197-6729
2042-3195