True smile recognition system using neural networks
| Autor: | Miyoko Nakano, Norio Akamatsu, Minoru Fukumi, Yasue Mitsukura |
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| Rok vydání: | 2004 |
| Předmět: |
Facial expression
Artificial neural network Computer science business.industry Speech recognition Interface (computing) Pattern recognition Facial recognition system ComputingMethodologies_PATTERNRECOGNITION Eigenface Face (geometry) Principal component analysis Artificial intelligence business Eigenvalues and eigenvectors Curse of dimensionality |
| Zdroj: | Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02.. |
| DOI: | 10.1109/iconip.2002.1198138 |
| Popis: | Recently, research about man-machine interfaces has increased. Therefore application to facial expressions is expected from the development of the man-machine interface. An eigen-face method is popular in these research fields by using the principal component analysis (PCA). But in PCA, it is not easy to compute eigenvectors with a large matrix when considering the cost of calculation to adapt for time-varying processing. In order for PCA to become high-speed, the simple principal component analysis (SPCA) is applied to compress the dimensionality of portions that constitute a face. A value of cos /spl theta/ is calculated using the eigenvector and the gray-scale image vector of each picture pattern. By using neural networks (NN), the value of cos /spl theta/ between true and false (plastic) smiles is clarified and the true smile is discriminated. Finally, in order to show the effectiveness of the proposed face classification method for true or false smile, computer simulations are done. |
| Databáze: | OpenAIRE |
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