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Cited by 160

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Facial Expression Recognition Using Constructive Feedforward Neural Networks

Ma, L., Khorasani, K.·2004·IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)
DOI 10.1109/tsmcb.2004.825930
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Abstract

A new technique for facial expression recognition is proposed, which uses the two-dimensional (2D) discrete cosine transform (DCT) over the entire face image as a feature detector and a constructive one-hidden-layer feedforward neural network as a facial expression classifier. An input-side pruning technique, proposed previously by the authors, is also incorporated into the constructive learning process to reduce the network size without sacrificing the performance of the resulting network. The proposed technique is applied to a database consisting of images of 60 men, each having five facial expression images (neutral, smile, anger, sadness, and surprise). Images of 40 men are used for network training, and the remaining images of 20 men are used for generalization and testing. Confusion matrices calculated in both network training and generalization for four facial expressions (smile, anger, sadness, and surprise) are used to evaluate the performance of the trained network. It is demonstrated that the best recognition rates are 100% and 93.75% (without rejection), for the training and generalizing images, respectively. Furthermore, the input-side weights of the constructed network are reduced by approximately 30% using our pruning method. In comparison with the fixed structure back propagation-based recognition methods in the literature, the proposed technique constructs one-hidden-layer feedforward neural network with fewer number of hidden units and weights, while simulta…

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Citations

Cites

Research works printed but not linked: 25

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Metadata

Authors
Ma, L., & Khorasani, K.
Venue
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2004-06
Volume
34
Issue
3
Pages
1588-1595
ISSN
1083-4419
DOI
10.1109/tsmcb.2004.825930
Cited by
160
References
2
Language
en

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