Skin detection: A bayesian network approach

Nicu Sebe; Ira Cohen; Thomas S. Huang; Theo Gevers

doi:10.1109/icpr.2004.1334405

Skin detection: A bayesian network approach

Nicu Sebe, Ira Cohen, Thomas S. Huang, Theo Gevers

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Research output: Contribution to journal › Conference article › peer-review

Abstract

The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach for skin detection. We test several classifiers and propose a methodology for incorporating unlabeled data. We apply the semi-supervised approach to skin detection and we show that learning the structure of Bayesian network classifiers enables learning good classifiers with a small labeled set and a large unlabeled set.

Original language	English (US)
Pages (from-to)	903-906
Number of pages	4
Journal	Proceedings - International Conference on Pattern Recognition
Volume	2
DOIs	https://doi.org/10.1109/icpr.2004.1334405
State	Published - 2004
Event	Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom Duration: Aug 23 2004 → Aug 26 2004

ASJC Scopus subject areas

Computer Vision and Pattern Recognition

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10.1109/icpr.2004.1334405

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title = "Skin detection: A bayesian network approach",

abstract = "The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach for skin detection. We test several classifiers and propose a methodology for incorporating unlabeled data. We apply the semi-supervised approach to skin detection and we show that learning the structure of Bayesian network classifiers enables learning good classifiers with a small labeled set and a large unlabeled set.",

author = "Nicu Sebe and Ira Cohen and Huang, {Thomas S.} and Theo Gevers",

year = "2004",

doi = "10.1109/icpr.2004.1334405",

language = "English (US)",

volume = "2",

pages = "903--906",

journal = "Proceedings - International Conference on Pattern Recognition",

issn = "1051-4651",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 ; Conference date: 23-08-2004 Through 26-08-2004",

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TY - JOUR

T1 - Skin detection

T2 - Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004

AU - Sebe, Nicu

AU - Cohen, Ira

AU - Huang, Thomas S.

AU - Gevers, Theo

PY - 2004

Y1 - 2004

N2 - The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach for skin detection. We test several classifiers and propose a methodology for incorporating unlabeled data. We apply the semi-supervised approach to skin detection and we show that learning the structure of Bayesian network classifiers enables learning good classifiers with a small labeled set and a large unlabeled set.

AB - The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach for skin detection. We test several classifiers and propose a methodology for incorporating unlabeled data. We apply the semi-supervised approach to skin detection and we show that learning the structure of Bayesian network classifiers enables learning good classifiers with a small labeled set and a large unlabeled set.

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U2 - 10.1109/icpr.2004.1334405

DO - 10.1109/icpr.2004.1334405

M3 - Conference article

AN - SCOPUS:10044249813

SN - 1051-4651

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SP - 903

EP - 906

JO - Proceedings - International Conference on Pattern Recognition

JF - Proceedings - International Conference on Pattern Recognition

Y2 - 23 August 2004 through 26 August 2004

ER -

Skin detection: A bayesian network approach

Abstract

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