Real-Time Pedestrian Tracking and Counting with TLD. (29th October 2018)

• Record Type: Journal Article
• Authors: Shi, Jiawei; Wang, Xianmei; Xiao, Huer
• Other Names: Simonelli Fulvio Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2018(2018)
• Publication Date: 2018-10-29
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2018/8486906
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : 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.