DocumentCode
1913734
Title
Understanding presumption system from facial images
Author
Mimura, Atsushi ; Hagiwata, M.
Author_Institution
Keio Univ., Yokohama, Japan
Volume
5
fYear
1999
fDate
1999
Firstpage
3270
Abstract
In this paper, we propose an understanding presumption system from facial images using a three-layered neural network. It can presume a degree of understanding from facial expressions; it can recognize whether a person understands a question or not. Feature points are located on each facial image and are used to extract an expression information. The expression information is given as an input and the system presumes the degree of understanding based on the facial images into 5 levels, from NOT UNDERSTAND to WELL UNDERSTAND. The network is learned using backpropagation algorithm. The average presumption rates of the proposed system was 71.3%
Keywords
backpropagation; face recognition; multilayer perceptrons; backpropagation; facial images; learning; three-layered neural network; understanding presumption system; Cameras; Data mining; Face recognition; Feature extraction; Humans; Neural networks; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.836181
Filename
836181
Link To Document