Adaptively adjusted gaussian mixture models for surveillance applications

Tianci Huang; Xiangzhong Fang; Jingbang Qiu; Takeshi Ikenaga

doi:10.1007/978-3-642-11301-7_70

Adaptively adjusted gaussian mixture models for surveillance applications

Tianci Huang^*, Xiangzhong Fang, Jingbang Qiu, Takeshi Ikenaga

^*Corresponding author for this work

Graduate School of Information, Production and Systems

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

5 Citations (Scopus)

Abstract

Segmentation of moving objects is the basic step for surveillance system. The Gaussian Mixture Model is one of the best models to cope with repetitive motions in a dynamic and complex environment. In this paper, an Adaptively Adjustment Mechanism was proposed by fully utilizing Gaussian distributions with least number so as to save the amount of computation. In addition to that, by applying proposed Gaussian Mixture Model scheme to edge segmented image and combining with data fusion method, the proposed algorithm was able to resist illumination change in scene and remove shadows of motion. Experiments proved the excellent performance.

Original language	English
Title of host publication	Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings
Pages	689-694
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-642-11301-7_70
Publication status	Published - 2009 Dec 1
Event	16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010 - Chongqing, China Duration: 2010 Oct 6 → 2010 Oct 8

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5916 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010
Country/Territory	China
City	Chongqing
Period	10/10/6 → 10/10/8

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-11301-7_70

Cite this

Huang, T., Fang, X., Qiu, J., & Ikenaga, T. (2009). Adaptively adjusted gaussian mixture models for surveillance applications. In Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings (pp. 689-694). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5916 LNCS). https://doi.org/10.1007/978-3-642-11301-7_70

Adaptively adjusted gaussian mixture models for surveillance applications. / Huang, Tianci; Fang, Xiangzhong; Qiu, Jingbang et al.
Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings. 2009. p. 689-694 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5916 LNCS).

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

Huang, T, Fang, X, Qiu, J & Ikenaga, T 2009, Adaptively adjusted gaussian mixture models for surveillance applications. in Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5916 LNCS, pp. 689-694, 16th International Multimedia Modeling Conference on Advances in Multimedia Modeling, MMM 2010, Chongqing, China, 10/10/6. https://doi.org/10.1007/978-3-642-11301-7_70

Huang T, Fang X, Qiu J, Ikenaga T. Adaptively adjusted gaussian mixture models for surveillance applications. In Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings. 2009. p. 689-694. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-11301-7_70

Huang, Tianci ; Fang, Xiangzhong ; Qiu, Jingbang et al. / Adaptively adjusted gaussian mixture models for surveillance applications. Advances in Multimedia Modeling - 16th International Multimedia Modeling Conference, MMM 2010, Proceedings. 2009. pp. 689-694 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Adaptively adjusted gaussian mixture models for surveillance applications

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