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 |
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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 | |
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 |
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Country | United States |
City | Honolulu |
Period | 99/7/10 → 99/7/15 |
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Materials Science (miscellaneous)