People tracking and abnormal situation detection in the open space

Shen Chuan Tai; Hung Hsiang Wang; Yu Tzu Chen

doi:10.1109/WIRLES.2005.1549612

People tracking and abnormal situation detection in the open space

Shen Chuan Tai, Hung Hsiang Wang, Yu Tzu Chen

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Recently, social security problem in the public place is more important, ex. Stealing, losing and some dangerous action, and how to detect and prevent them on demand now is an important task. In this paper, we present a method of tracking objects and detecting abnormal situation in the open space. Usually, background model will determine a robust foreground region. Therefore, we first propose a new algorithm to estimate background. Then, a new tracking people algorithm will propose. It not only can track people, but also can recognize people from merge to split. Final, we will detect abnormal situation in the open space. The method is computationally fast enough to track people in real time.

Original language	English
Title of host publication	2005 International Conference on Wireless Networks, Communications and Mobile Computing
Pages	1367-1370
Number of pages	4
DOIs	https://doi.org/10.1109/WIRLES.2005.1549612
Publication status	Published - 2005 Dec 1
Event	2005 International Conference on Wireless Networks, Communications and Mobile Computing - Maui, HI, United States Duration: 2005 Jun 13 → 2005 Jun 16

Publication series

Name	2005 International Conference on Wireless Networks, Communications and Mobile Computing
Volume	2

Other

Other	2005 International Conference on Wireless Networks, Communications and Mobile Computing
Country	United States
City	Maui, HI
Period	05-06-13 → 05-06-16

All Science Journal Classification (ASJC) codes

Engineering(all)

Access to Document

10.1109/WIRLES.2005.1549612

Cite this

Tai, S. C., Wang, H. H., & Chen, Y. T. (2005). People tracking and abnormal situation detection in the open space. In 2005 International Conference on Wireless Networks, Communications and Mobile Computing (pp. 1367-1370). [1549612] (2005 International Conference on Wireless Networks, Communications and Mobile Computing; Vol. 2). https://doi.org/10.1109/WIRLES.2005.1549612

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title = "People tracking and abnormal situation detection in the open space",

abstract = "Recently, social security problem in the public place is more important, ex. Stealing, losing and some dangerous action, and how to detect and prevent them on demand now is an important task. In this paper, we present a method of tracking objects and detecting abnormal situation in the open space. Usually, background model will determine a robust foreground region. Therefore, we first propose a new algorithm to estimate background. Then, a new tracking people algorithm will propose. It not only can track people, but also can recognize people from merge to split. Final, we will detect abnormal situation in the open space. The method is computationally fast enough to track people in real time.",

author = "Tai, {Shen Chuan} and Wang, {Hung Hsiang} and Chen, {Yu Tzu}",

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Tai, SC, Wang, HH & Chen, YT 2005, People tracking and abnormal situation detection in the open space. in 2005 International Conference on Wireless Networks, Communications and Mobile Computing., 1549612, 2005 International Conference on Wireless Networks, Communications and Mobile Computing, vol. 2, pp. 1367-1370, 2005 International Conference on Wireless Networks, Communications and Mobile Computing, Maui, HI, United States, 05-06-13. https://doi.org/10.1109/WIRLES.2005.1549612

People tracking and abnormal situation detection in the open space. / Tai, Shen Chuan; Wang, Hung Hsiang; Chen, Yu Tzu.

2005 International Conference on Wireless Networks, Communications and Mobile Computing. 2005. p. 1367-1370 1549612 (2005 International Conference on Wireless Networks, Communications and Mobile Computing; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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