Multicue HMM-UKF for real-time contour tracking

Yunqiang Chen; Yong Rui; Thomas S. Huang

doi:10.1109/TPAMI.2006.190

Multicue HMM-UKF for real-time contour tracking

Yunqiang Chen, Yong Rui, Thomas S. Huang

Research output: Contribution to journal › Article › peer-review

Abstract

We propose an HMM model for contour detection based on multiple visual cues in spatial domain and improve it by joint probabilistic matching to reduce background clutter. It is further integrated with unscented Kalman filter to exploit object dynamics in nonlinear systems for robust contour tracking.

Original language	English (US)
Pages (from-to)	1525-1529
Number of pages	5
Journal	IEEE transactions on pattern analysis and machine intelligence
Volume	28
Issue number	9
DOIs	https://doi.org/10.1109/TPAMI.2006.190
State	Published - Sep 2006
Externally published	Yes

Keywords

HMM
Joint probabilistic matching
Parametric contour
Unscented Kalman filters

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

Online availability

10.1109/TPAMI.2006.190

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title = "Multicue HMM-UKF for real-time contour tracking",

abstract = "We propose an HMM model for contour detection based on multiple visual cues in spatial domain and improve it by joint probabilistic matching to reduce background clutter. It is further integrated with unscented Kalman filter to exploit object dynamics in nonlinear systems for robust contour tracking.",

keywords = "HMM, Joint probabilistic matching, Parametric contour, Unscented Kalman filters",

author = "Yunqiang Chen and Yong Rui and Huang, {Thomas S.}",

year = "2006",

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AU - Huang, Thomas S.

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KW - Parametric contour

KW - Unscented Kalman filters

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Multicue HMM-UKF for real-time contour tracking

Abstract

Keywords

ASJC Scopus subject areas

Online availability

Library availability

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