Multiple pedestrian detection and tracking based on weighted temporal texture features

Hee Deok Yang, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper presents a novel method for detecting and tracking pedestrians from video images taken by a fixed camera. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. Experimental results with various real video data revealed that real time pedestrian detection and tracking is possible with increased stability over 5-15% even under occasional occlusions in video surveillance applications.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages248-251
Number of pages4
Volume4
DOIs
Publication statusPublished - 2004 Dec 20
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 2004 Aug 232004 Aug 26

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period04/8/2304/8/26

Fingerprint

Textures
Identification (control systems)
Cameras
Color

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Cite this

Yang, H. D., & Lee, S. W. (2004). Multiple pedestrian detection and tracking based on weighted temporal texture features. In J. Kittler, M. Petrou, & M. Nixon (Eds.), Proceedings - International Conference on Pattern Recognition (Vol. 4, pp. 248-251) https://doi.org/10.1109/ICPR.2004.1333750

Multiple pedestrian detection and tracking based on weighted temporal texture features. / Yang, Hee Deok; Lee, Seong Whan.

Proceedings - International Conference on Pattern Recognition. ed. / J. Kittler; M. Petrou; M. Nixon. Vol. 4 2004. p. 248-251.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yang, HD & Lee, SW 2004, Multiple pedestrian detection and tracking based on weighted temporal texture features. in J Kittler, M Petrou & M Nixon (eds), Proceedings - International Conference on Pattern Recognition. vol. 4, pp. 248-251, Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, United Kingdom, 04/8/23. https://doi.org/10.1109/ICPR.2004.1333750
Yang HD, Lee SW. Multiple pedestrian detection and tracking based on weighted temporal texture features. In Kittler J, Petrou M, Nixon M, editors, Proceedings - International Conference on Pattern Recognition. Vol. 4. 2004. p. 248-251 https://doi.org/10.1109/ICPR.2004.1333750
Yang, Hee Deok ; Lee, Seong Whan. / Multiple pedestrian detection and tracking based on weighted temporal texture features. Proceedings - International Conference on Pattern Recognition. editor / J. Kittler ; M. Petrou ; M. Nixon. Vol. 4 2004. pp. 248-251
@inproceedings{594b97f1c9f84cd59f3a65e2ac1ddd3d,
title = "Multiple pedestrian detection and tracking based on weighted temporal texture features",
abstract = "This paper presents a novel method for detecting and tracking pedestrians from video images taken by a fixed camera. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. Experimental results with various real video data revealed that real time pedestrian detection and tracking is possible with increased stability over 5-15{\%} even under occasional occlusions in video surveillance applications.",
author = "Yang, {Hee Deok} and Lee, {Seong Whan}",
year = "2004",
month = "12",
day = "20",
doi = "10.1109/ICPR.2004.1333750",
language = "English",
isbn = "0769521282",
volume = "4",
pages = "248--251",
editor = "J. Kittler and M. Petrou and M. Nixon",
booktitle = "Proceedings - International Conference on Pattern Recognition",

}

TY - GEN

T1 - Multiple pedestrian detection and tracking based on weighted temporal texture features

AU - Yang, Hee Deok

AU - Lee, Seong Whan

PY - 2004/12/20

Y1 - 2004/12/20

N2 - This paper presents a novel method for detecting and tracking pedestrians from video images taken by a fixed camera. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. Experimental results with various real video data revealed that real time pedestrian detection and tracking is possible with increased stability over 5-15% even under occasional occlusions in video surveillance applications.

AB - This paper presents a novel method for detecting and tracking pedestrians from video images taken by a fixed camera. A pedestrian may be totally or partially occluded in a scene for some period of time. The proposed approach uses the appearance model for the identification of pedestrians and the weighted temporal texture features. We compared the proposed method with other related methods using color and shape features, and analyzed the features' stability. Experimental results with various real video data revealed that real time pedestrian detection and tracking is possible with increased stability over 5-15% even under occasional occlusions in video surveillance applications.

UR - http://www.scopus.com/inward/record.url?scp=10044224337&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=10044224337&partnerID=8YFLogxK

U2 - 10.1109/ICPR.2004.1333750

DO - 10.1109/ICPR.2004.1333750

M3 - Conference contribution

SN - 0769521282

VL - 4

SP - 248

EP - 251

BT - Proceedings - International Conference on Pattern Recognition

A2 - Kittler, J.

A2 - Petrou, M.

A2 - Nixon, M.

ER -