Real time multi-object tracking using TLD framework

Sharma, Swati; Khachane, Ajitkumar; Motwani, Dilip

doi:10.1109/inventive.2016.7824839

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Multipedestrian Patch Obtaining1

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2018

2021

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Cited by 4 publications

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“…Zhou et al [11] proposed PE-TLD, after the process of ViBe and variance filter, hog features, and SVM classifier were used for automatic targets recognition. Besides, S. Sharma et al [12] let users manually select the desired tracking objects in the initialization process.…”

Section: Multipedestrian Patch Obtainingmentioning

confidence: 99%

Real-Time Pedestrian Tracking and Counting with TLD

Shi

Wang

Xiao

2018

Journal of Advanced Transportation

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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.

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Section: Multipedestrian Patch Obtainingmentioning

confidence: 99%