Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image

Takakazu Chashikawa; Keizo Fujii; Yoshiyasu Takefuji

doi:10.1109/IPMM.1999.792522

Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image

Takakazu Chashikawa, Keizo Fujii, Yoshiyasu Takefuji

Faculty of Environment and Information Studies

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

Abstract

This paper proposes a neural network system to detect human faces. Our scheme is composed of a preprocess and KenzanNET. Preprocessing analyzes hyperspectral images by using a hybrid self-organizing classification model to extract skin area and making a facial candidate pattern based on the extracted skin area. KenzanNET discriminate a face from other body parts. KenzanNET is a kind of feed forward neural network and is made from CombNET [ I[ improved by an additional learning function. Under the various conditions in terms of background and brightness in a room and the distance between people and camera, our system can detect human face with 76.9% accuracy.

Original language	English
Title of host publication	Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	453-458
Number of pages	6
Volume	1
ISBN (Electronic)	0780354893, 9780780354890
DOIs	https://doi.org/10.1109/IPMM.1999.792522
Publication status	Published - 1999 Jan 1
Event	2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999 - Honolulu, United States Duration: 1999 Jul 10 → 1999 Jul 15

Other

Other	2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999
Country	United States
City	Honolulu
Period	99/7/10 → 99/7/15

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Materials Science (miscellaneous)

Access to Document

10.1109/IPMM.1999.792522

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Chashikawa, T., Fujii, K., & Takefuji, Y. (1999). Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image. In Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999 (Vol. 1, pp. 453-458). [792522] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPMM.1999.792522

Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image. / Chashikawa, Takakazu; Fujii, Keizo; Takefuji, Yoshiyasu.

Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. Vol. 1 Institute of Electrical and Electronics Engineers Inc., 1999. p. 453-458 792522.

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

Chashikawa, T, Fujii, K & Takefuji, Y 1999, Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image. in Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. vol. 1, 792522, Institute of Electrical and Electronics Engineers Inc., pp. 453-458, 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999, Honolulu, United States, 99/7/10. https://doi.org/10.1109/IPMM.1999.792522

Chashikawa T, Fujii K, Takefuji Y. Human Face Detection System by Kenzan NET with preprocess analyzing hyperspectral image. In Proceedings of the 2nd International Conference on Intelligent Processing and Manufacturing of Materials, IPMM 1999. Vol. 1. Institute of Electrical and Electronics Engineers Inc. 1999. p. 453-458. 792522 https://doi.org/10.1109/IPMM.1999.792522

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abstract = "This paper proposes a neural network system to detect human faces. Our scheme is composed of a preprocess and KenzanNET. Preprocessing analyzes hyperspectral images by using a hybrid self-organizing classification model to extract skin area and making a facial candidate pattern based on the extracted skin area. KenzanNET discriminate a face from other body parts. KenzanNET is a kind of feed forward neural network and is made from CombNET [ I[ improved by an additional learning function. Under the various conditions in terms of background and brightness in a room and the distance between people and camera, our system can detect human face with 76.9% accuracy.",

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