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Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis

Chung, Koon Yin C.
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428

Abstract Details

2010, Master of Science (MS), Ohio University, Computer Science (Engineering and Technology).
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.
David M. Chelberg, PhD (Advisor)
Jun Dong Liu, PhD (Committee Member)
Frank Drews, PhD (Committee Member)
69 p.
Computer Science; Electrical Engineering; Engineering
Facial Expression Recognition; Gabor; Kernel Principal Component Analysis; KPCA; Class Mean Gabor Responses

Recommended Citations

Citations

  • Chung, K. Y. C. (2010). Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428

    APA Style (7th edition)

  • Chung, Koon Yin. Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis. 2010. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428.

    MLA Style (8th edition)

  • Chung, Koon Yin. "Facial Expression Recognition by Using Class Mean Gabor Responses with Kernel Principal Component Analysis." Master's thesis, Ohio University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1260468428

    Chicago Manual of Style (17th edition)

ohiou1260468428
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© 2009, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.