New fuzzy skin model for face detection

Moon Hwan Kim, Jin Bae Park, Young Hoon Joo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

We discuss the face detection method by using skin information. Skin color has proven to be a useful and robust cue for face detection, localization and tracking. Numerous techniques for skin color modelling and recognition have been proposed during several past years. In this paper we propose a new fuzzy skin model for face detection and its identification method. The fuzzy skin model comprise of the fuzzy rules with color information. The membership function and structure of fuzzy rule are identified by the proposed linear matrix inequality method. Experimental results demonstrate successful face detection.

Original languageEnglish
Title of host publicationAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings
Pages557-566
Number of pages10
Volume3809 LNAI
Publication statusPublished - 2005 Dec 1
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 2005 Dec 52005 Dec 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
CountryAustralia
CitySydney
Period05/12/505/12/9

Fingerprint

Face Detection
Face recognition
Skin
Fuzzy rules
Fuzzy Rules
Color
Model
Membership functions
Linear matrix inequalities
Membership Function
Matrix Inequality
Linear Inequalities
Identification (control systems)
Experimental Results
Modeling
Demonstrate

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kim, M. H., Park, J. B., & Joo, Y. H. (2005). New fuzzy skin model for face detection. In AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings (Vol. 3809 LNAI, pp. 557-566). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI).
Kim, Moon Hwan ; Park, Jin Bae ; Joo, Young Hoon. / New fuzzy skin model for face detection. AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings. Vol. 3809 LNAI 2005. pp. 557-566 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Kim, MH, Park, JB & Joo, YH 2005, New fuzzy skin model for face detection. in AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings. vol. 3809 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3809 LNAI, pp. 557-566, 18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence, Sydney, Australia, 05/12/5.

New fuzzy skin model for face detection. / Kim, Moon Hwan; Park, Jin Bae; Joo, Young Hoon.

AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings. Vol. 3809 LNAI 2005. p. 557-566 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - We discuss the face detection method by using skin information. Skin color has proven to be a useful and robust cue for face detection, localization and tracking. Numerous techniques for skin color modelling and recognition have been proposed during several past years. In this paper we propose a new fuzzy skin model for face detection and its identification method. The fuzzy skin model comprise of the fuzzy rules with color information. The membership function and structure of fuzzy rule are identified by the proposed linear matrix inequality method. Experimental results demonstrate successful face detection.

AB - We discuss the face detection method by using skin information. Skin color has proven to be a useful and robust cue for face detection, localization and tracking. Numerous techniques for skin color modelling and recognition have been proposed during several past years. In this paper we propose a new fuzzy skin model for face detection and its identification method. The fuzzy skin model comprise of the fuzzy rules with color information. The membership function and structure of fuzzy rule are identified by the proposed linear matrix inequality method. Experimental results demonstrate successful face detection.

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Kim MH, Park JB, Joo YH. New fuzzy skin model for face detection. In AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings. Vol. 3809 LNAI. 2005. p. 557-566. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).