article

Detecting and tracking of multiple pedestrians using motion, color information and the AdaBoost algorithm

Authors:

Wookhyun KimAuthors Info & Claims

Multimedia Tools and Applications, Volume 65, Issue 1

Pages 161 - 179

https://doi.org/10.1007/s11042-012-1156-3

Published: 01 July 2013 Publication History

Abstract

Robust detection and tracking of pedestrians in image sequences are essential for many vision applications. In this paper, we propose a method to detect and track multiple pedestrians using motion, color information and the AdaBoost algorithm. Our approach detects pedestrians in a walking pose from a single camera on a mobile or stationary system. In the case of mobile systems, ego-motion of the camera is compensated for by corresponding feature sets. The region of interest is calculated by the difference image between two consecutive images using the compensated image. Pedestrian detector is learned by boosting a number of weak classifiers which are based on Histogram of Oriented Gradient (HOG) features. Pedestrians are tracked by block matching method using color information. Our tracking system can track pedestrians with possibly partial occlusions and without misses using information stored in advance even after occlusion is ended. The proposed approach has been tested on a number of image sequences, and was shown to detect and track multiple pedestrians very well.

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Cited By

Liu BLi XXiao YSun PZhao SPeng TZheng ZHuang Y(2024)Adaboost-based SVDD for anomaly detection with dictionary learningExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121770238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121770
Lahmyed REl Ansari MKerkaou Z(2022)A novel visible spectrum images-based pedestrian detection and tracking system for surveillance in non-controlled environmentsMultimedia Tools and Applications10.1007/s11042-022-13026-481:27(39275-39309)Online publication date: 1-Nov-2022
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Mathivanan APalaniswamy S(2022)Efficient fuzzy feature matching and optimal feature points for multiple objects tracking in fixed and active camera modelsMultimedia Tools and Applications10.1007/s11042-019-07825-578:19(27245-27270)Online publication date: 10-Mar-2022
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Detecting and tracking of multiple pedestrians using motion, color information and the AdaBoost algorithm
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cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 65, Issue 1

July 2013

175 pages

ISSN:1380-7501

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Copyright © Copyright © 2013 Springer Science+Business Media New York.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2013

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Cited By

Liu BLi XXiao YSun PZhao SPeng TZheng ZHuang Y(2024)Adaboost-based SVDD for anomaly detection with dictionary learningExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121770238:PCOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121770
Lahmyed REl Ansari MKerkaou Z(2022)A novel visible spectrum images-based pedestrian detection and tracking system for surveillance in non-controlled environmentsMultimedia Tools and Applications10.1007/s11042-022-13026-481:27(39275-39309)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s11042-022-13026-4
Mathivanan APalaniswamy S(2022)Efficient fuzzy feature matching and optimal feature points for multiple objects tracking in fixed and active camera modelsMultimedia Tools and Applications10.1007/s11042-019-07825-578:19(27245-27270)Online publication date: 10-Mar-2022
https://dl.acm.org/doi/10.1007/s11042-019-07825-5
Jindal AAggarwal NGupta S(2018)An Obstacle Detection Method for Visually Impaired Persons by Ground Plane Removal Using Speeded-Up Robust Features and Gray Level Co-Occurrence MatrixPattern Recognition and Image Analysis10.1134/S105466181802008628:2(288-300)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.1134/S1054661818020086
Farajzadeh NKaramiani AHashemzadeh M(2018)A fast and accurate moving object tracker in active camera modelMultimedia Tools and Applications10.1007/s11042-017-4597-x77:6(6775-6797)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1007/s11042-017-4597-x
Hashemzadeh MFarajzadeh N(2016)Combining keypoint-based and segment-based features for counting people in crowded scenesInformation Sciences: an International Journal10.1016/j.ins.2016.01.060345:C(199-216)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1016/j.ins.2016.01.060
Karamiani AFarajzadeh N(2016)Optimal feature points for tracking multiple moving objects in active camera modelMultimedia Tools and Applications10.1007/s11042-015-2823-y75:18(10999-11017)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1007/s11042-015-2823-y
Zhang SKlein DBauckhage CCremers A(2016)Fast moving pedestrian detection based on motion segmentation and new motion featuresMultimedia Tools and Applications10.1007/s11042-015-2571-z75:11(6263-6282)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1007/s11042-015-2571-z
Zhao YZhou ZXu M(2015)Forest fire smoke video detection using spatiotemporal and dynamic texture featuresJournal of Electrical and Computer Engineering10.1155/2015/7061872015(40-40)Online publication date: 1-Jan-2015
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Zhang TYang ZJia WWu QYang JHe X(2015)Fast and robust head detection with arbitrary pose and occlusionMultimedia Tools and Applications10.1007/s11042-014-2110-374:21(9365-9385)Online publication date: 1-Nov-2015
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