Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis
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Ohio University / OhioLINK
2010
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ohiou12604684282021-08-03T05:46:29Z Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis Chung, Koon Yin C. Computer Science Electrical Engineering Engineering Facial Expression Recognition Gabor Kernel Principal Component Analysis KPCA Class Mean Gabor Responses This thesis presents a novel approach for recognizing facial expressions by incorporating class-mean Gabor responses of sampled images of human facial expressions and kernel principal component analysis (kernel PCA) with fractional polynomial power models. A mean vector of features is obtained with Gabor filters from a class of images instead of the more common method in which features are obtained from individual images. The computational cost of spatial convolutions on mean features of a class is less than the same type of convolutions with individual features. The dimensionality of mean features from Gabor filters is further reduced by using a kernel PCA technique with polynomial kernels. The kernel PCA technique is extended to use fractional power polynomial models for facial expression recognition. The proposed approach has the advantage of doing fewer projections than other facial expression recognition approaches that use traditional kernel PCA models. The proposed approach of class-mean Gabor responses has higher accuracy than existing systems that use the kernel PCA technique with class-mean image responses only. 2010-04-16 English text Ohio University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428 http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Computer Science Electrical Engineering Engineering Facial Expression Recognition Gabor Kernel Principal Component Analysis KPCA Class Mean Gabor Responses |
| spellingShingle |
Computer Science Electrical Engineering Engineering Facial Expression Recognition Gabor Kernel Principal Component Analysis KPCA Class Mean Gabor Responses Chung, Koon Yin C. Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis |
| author |
Chung, Koon Yin C. |
| author_facet |
Chung, Koon Yin C. |
| author_sort |
Chung, Koon Yin C. |
| title |
Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis |
| title_short |
Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis |
| title_full |
Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis |
| title_fullStr |
Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis |
| title_full_unstemmed |
Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis |
| title_sort |
facial expression recognition by using class mean gabor responses with kernel principal component analysis |
| publisher |
Ohio University / OhioLINK |
| publishDate |
2010 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428 |
| work_keys_str_mv |
AT chungkoonyinc facialexpressionrecognitionbyusingclassmeangaborresponseswithkernelprincipalcomponentanalysis |
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1719425046702718976 |