Object tracking using adaptive colour mixture models

Stephen J. McKenna; Yogesh  Raja; Shaogang Gong

doi:10.1007/3-540-63930-6_174

Object tracking using adaptive colour mixture models

Stephen J. McKenna (Lead / Corresponding author), Yogesh Raja (Lead / Corresponding author), Shaogang Gong (Lead / Corresponding author)

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

31 Citations (Scopus)

Abstract

The use of adaptive Gaussian mixtures to model the colour distributions of objects is described. These models are used to perform robust, real-time tracking under varying illumination, viewing geometry and camera parameters. Observed log-likelihood measurements were used to perform selective adaptation.

Original language	English
Title of host publication	Computer Vision — ACCV'98
Subtitle of host publication	Third Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings
Editors	Roland Chin, Ting-Chuen Pong
Place of Publication	Berlin
Publisher	Springer
Pages	615-622
Number of pages	8
Volume	1
ISBN (Electronic)	9783540696698
ISBN (Print)	9783540639305
DOIs	https://doi.org/10.1007/3-540-63930-6_174
Publication status	Published - 1998
Event	3rd Asian Conference on Computer Vision - Hong Kong University of Science & Technology (HKUST), Hong Kong, Hong Kong Duration: 8 Jan 1998 → 10 Jan 1998 http://www.cse.ust.hk/accv98/

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Volume	1351
ISSN (Print)	0302-9743

Conference

Conference	3rd Asian Conference on Computer Vision
Abbreviated title	ACCV'98
Country/Territory	Hong Kong
City	Hong Kong
Period	8/01/98 → 10/01/98
Internet address	http://www.cse.ust.hk/accv98/

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10.1007/3-540-63930-6_174

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McKenna, S. J., Raja, Y., & Gong, S. (1998). Object tracking using adaptive colour mixture models. In R. Chin, & T.-C. Pong (Eds.), Computer Vision — ACCV'98: Third Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings (Vol. 1, pp. 615-622). (Lecture notes in computer science; Vol. 1351). Springer . https://doi.org/10.1007/3-540-63930-6_174

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title = "Object tracking using adaptive colour mixture models",

abstract = "The use of adaptive Gaussian mixtures to model the colour distributions of objects is described. These models are used to perform robust, real-time tracking under varying illumination, viewing geometry and camera parameters. Observed log-likelihood measurements were used to perform selective adaptation.",

author = "McKenna, {Stephen J.} and Yogesh Raja and Shaogang Gong",

year = "1998",

doi = "10.1007/3-540-63930-6_174",

language = "English",

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publisher = "Springer ",

pages = "615--622",

editor = "Chin, {Roland } and Pong, {Ting-Chuen }",

booktitle = "Computer Vision — ACCV'98",

note = "3rd Asian Conference on Computer Vision , ACCV'98 ; Conference date: 08-01-1998 Through 10-01-1998",

url = "http://www.cse.ust.hk/accv98/",

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McKenna, SJ, Raja, Y & Gong, S 1998, Object tracking using adaptive colour mixture models. in R Chin & T-C Pong (eds), Computer Vision — ACCV'98: Third Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings. vol. 1, Lecture notes in computer science, vol. 1351, Springer , Berlin, pp. 615-622, 3rd Asian Conference on Computer Vision , Hong Kong, Hong Kong, 8/01/98. https://doi.org/10.1007/3-540-63930-6_174

Object tracking using adaptive colour mixture models. / McKenna, Stephen J. (Lead / Corresponding author); Raja, Yogesh (Lead / Corresponding author); Gong, Shaogang (Lead / Corresponding author).
Computer Vision — ACCV'98: Third Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings. ed. / Roland Chin; Ting-Chuen Pong. Vol. 1 Berlin: Springer , 1998. p. 615-622 (Lecture notes in computer science; Vol. 1351).

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

TY - GEN

T1 - Object tracking using adaptive colour mixture models

AU - McKenna, Stephen J.

AU - Raja, Yogesh

AU - Gong, Shaogang

PY - 1998

Y1 - 1998

N2 - The use of adaptive Gaussian mixtures to model the colour distributions of objects is described. These models are used to perform robust, real-time tracking under varying illumination, viewing geometry and camera parameters. Observed log-likelihood measurements were used to perform selective adaptation.

AB - The use of adaptive Gaussian mixtures to model the colour distributions of objects is described. These models are used to perform robust, real-time tracking under varying illumination, viewing geometry and camera parameters. Observed log-likelihood measurements were used to perform selective adaptation.

U2 - 10.1007/3-540-63930-6_174

DO - 10.1007/3-540-63930-6_174

M3 - Conference contribution

SN - 9783540639305

VL - 1

T3 - Lecture notes in computer science

SP - 615

EP - 622

BT - Computer Vision — ACCV'98

A2 - Chin, Roland

A2 - Pong, Ting-Chuen

PB - Springer

CY - Berlin

T2 - 3rd Asian Conference on Computer Vision

Y2 - 8 January 1998 through 10 January 1998

ER -

Object tracking using adaptive colour mixture models

Abstract

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