Application of a neural network in recognizing facial expression

Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The n...

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Bibliographic Details
Main Authors: Donohue, B.A., Bronzino, J.D., DiLiberti, J.H., Olson, D.P., Schweitzer, L.R., Walsh, P.
Format: Conference Proceeding
Language:English
Subjects:
Biomedical engineering
Biomedical imaging
Computed tomography
Face recognition
Hospitals
Humans
Intelligent networks
Neural networks
Pattern recognition
Time of arrival estimation
Online Access:Request full text
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Summary:Input to the neural network program consists of facial images from a video source. The program uses the back propagation algorithm to train the network and to classify input data based on the subject's posed facial expression. Training and testing were performed with multiple individuals. The network was trained on a set consisting of 34 happy and 34 sad images from five different subjects. Additionally, the network was tested with images of subjects which were not included in training. In this case, training was performed using 24 happy and 24 sad images of three subjects. Testing was performed using ten happy and ten sad images of two new subjects. In preliminary testing, the network responded correctly for 85% of the 20 test cases. The ability of the network to generalize this discrimination successfully to new individuals is also demonstrated.< >
DOI:10.1109/NEBC.1991.154648