A color-triangle-based approach to the detection of human face

Chiunhsiun Lin; Kuo Chin Fan

doi:10.1007/3-540-45482-9_36

A color-triangle-based approach to the detection of human face

Chiunhsiun Lin, Kuo Chin Fan

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

5 Scopus citations

Abstract

A robust and efficient human face detection system that can detect multiple faces in various surroundings is presented in this paper. The proposed system consists of two principal parts. The first part is to search for the potential face regions. The second part is to perform face verification task. Our system can conquer different size, different lighting condition, varying pose and expression, and noise and defocus problems. In addition to overcome the problem of partial occlusion of mouth and sunglasses, the color segmentation process can successfully extract skin color from complex backgrounds. Experimental results demonstrate that an approximately 98% success rate is achieved. The experimental results reveal that the proposed method is better than traditional methods in terms of efficiency and accuracy.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Tomaso Poggio, Seong-Whan Lee, Heinrich H. Bulthoff
Publisher	Springer Verlag
Pages	359-368
Number of pages	10
ISBN (Print)	3540675604, 9783540675600
DOIs	https://doi.org/10.1007/3-540-45482-9_36
State	Published - 2000
Event	1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000 - Seoul, Korea, Republic of Duration: 15 May 2000 → 17 May 2000

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1811
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000
Country/Territory	Korea, Republic of
City	Seoul
Period	15/05/00 → 17/05/00

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10.1007/3-540-45482-9_36

Cite this

Lin, C., & Fan, K. C. (2000). A color-triangle-based approach to the detection of human face. In T. Poggio, S-W. Lee, & H. H. Bulthoff (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 359-368). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1811). Springer Verlag. https://doi.org/10.1007/3-540-45482-9_36

Lin, Chiunhsiun ; Fan, Kuo Chin. / A color-triangle-based approach to the detection of human face. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Tomaso Poggio ; Seong-Whan Lee ; Heinrich H. Bulthoff. Springer Verlag, 2000. pp. 359-368 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "A robust and efficient human face detection system that can detect multiple faces in various surroundings is presented in this paper. The proposed system consists of two principal parts. The first part is to search for the potential face regions. The second part is to perform face verification task. Our system can conquer different size, different lighting condition, varying pose and expression, and noise and defocus problems. In addition to overcome the problem of partial occlusion of mouth and sunglasses, the color segmentation process can successfully extract skin color from complex backgrounds. Experimental results demonstrate that an approximately 98% success rate is achieved. The experimental results reveal that the proposed method is better than traditional methods in terms of efficiency and accuracy.",

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Lin, C & Fan, KC 2000, A color-triangle-based approach to the detection of human face. in T Poggio, S-W Lee & HH Bulthoff (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1811, Springer Verlag, pp. 359-368, 1st IEEE International Workshop on Biologically Motivated Computer Vision, BMCV 2000, Seoul, Korea, Republic of, 15/05/00. https://doi.org/10.1007/3-540-45482-9_36

A color-triangle-based approach to the detection of human face. / Lin, Chiunhsiun; Fan, Kuo Chin.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Tomaso Poggio; Seong-Whan Lee; Heinrich H. Bulthoff. Springer Verlag, 2000. p. 359-368 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1811).

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

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N2 - A robust and efficient human face detection system that can detect multiple faces in various surroundings is presented in this paper. The proposed system consists of two principal parts. The first part is to search for the potential face regions. The second part is to perform face verification task. Our system can conquer different size, different lighting condition, varying pose and expression, and noise and defocus problems. In addition to overcome the problem of partial occlusion of mouth and sunglasses, the color segmentation process can successfully extract skin color from complex backgrounds. Experimental results demonstrate that an approximately 98% success rate is achieved. The experimental results reveal that the proposed method is better than traditional methods in terms of efficiency and accuracy.

AB - A robust and efficient human face detection system that can detect multiple faces in various surroundings is presented in this paper. The proposed system consists of two principal parts. The first part is to search for the potential face regions. The second part is to perform face verification task. Our system can conquer different size, different lighting condition, varying pose and expression, and noise and defocus problems. In addition to overcome the problem of partial occlusion of mouth and sunglasses, the color segmentation process can successfully extract skin color from complex backgrounds. Experimental results demonstrate that an approximately 98% success rate is achieved. The experimental results reveal that the proposed method is better than traditional methods in terms of efficiency and accuracy.

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Lin C, Fan KC. A color-triangle-based approach to the detection of human face. In Poggio T, Lee S-W, Bulthoff HH, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2000. p. 359-368. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-45482-9_36

A color-triangle-based approach to the detection of human face

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