Adaptive visual tracking and recognition using particle filters

Shaohua Zhou; R. Chellappa; B. Moghaddam

doi:10.1109/ICME.2003.1221625

Adaptive visual tracking and recognition using particle filters

Shaohua Zhou, R. Chellappa, B. Moghaddam

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

Abstract

This paper presents an improved method for simultaneous tracking and recognition of human faces from video, where a time series model is used to resolve the uncertainties in tracking and recognition. The improvements mainly arise from three aspects: (i) modeling the inter-frame appearance changes within the video sequence using an adaptive appearance model and an adaptive-velocity motion model; (ii) modeling the appearance changes between the video frames and gallery images by constructing intra-and extra-personal spaces; and (iii) utilization of the fact that the gallery images are in frontal views. By embedding them in a particle filter, we are able to achieve a stabilized tracker and an accurate recognizer when confronted by pose and illumination variations.

Original language	English (US)
Title of host publication	Proceedings - 2003 International Conference on Multimedia and Expo, ICME
Publisher	IEEE Computer Society
Pages	349-352
Number of pages	4
ISBN (Electronic)	0780379659
DOIs	https://doi.org/10.1109/ICME.2003.1221625
State	Published - 2003
Externally published	Yes
Event	2003 International Conference on Multimedia and Expo, ICME 2003 - Baltimore, United States Duration: Jul 6 2003 → Jul 9 2003

Publication series

Name	Proceedings - IEEE International Conference on Multimedia and Expo
Volume	2
ISSN (Print)	1945-7871
ISSN (Electronic)	1945-788X

Other

Other	2003 International Conference on Multimedia and Expo, ICME 2003
Country/Territory	United States
City	Baltimore
Period	7/6/03 → 7/9/03

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications

Access to Document

10.1109/ICME.2003.1221625

Cite this

Adaptive visual tracking and recognition using particle filters. / Zhou, Shaohua; Chellappa, R.; Moghaddam, B.
Proceedings - 2003 International Conference on Multimedia and Expo, ICME. IEEE Computer Society, 2003. p. 349-352 1221625 (Proceedings - IEEE International Conference on Multimedia and Expo; Vol. 2).

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

Zhou, S, Chellappa, R & Moghaddam, B 2003, Adaptive visual tracking and recognition using particle filters. in Proceedings - 2003 International Conference on Multimedia and Expo, ICME., 1221625, Proceedings - IEEE International Conference on Multimedia and Expo, vol. 2, IEEE Computer Society, pp. 349-352, 2003 International Conference on Multimedia and Expo, ICME 2003, Baltimore, United States, 7/6/03. https://doi.org/10.1109/ICME.2003.1221625

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author = "Shaohua Zhou and R. Chellappa and B. Moghaddam",

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AB - This paper presents an improved method for simultaneous tracking and recognition of human faces from video, where a time series model is used to resolve the uncertainties in tracking and recognition. The improvements mainly arise from three aspects: (i) modeling the inter-frame appearance changes within the video sequence using an adaptive appearance model and an adaptive-velocity motion model; (ii) modeling the appearance changes between the video frames and gallery images by constructing intra-and extra-personal spaces; and (iii) utilization of the fact that the gallery images are in frontal views. By embedding them in a particle filter, we are able to achieve a stabilized tracker and an accurate recognizer when confronted by pose and illumination variations.

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ER -

Adaptive visual tracking and recognition using particle filters

Abstract

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ASJC Scopus subject areas

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