Face recognition based on global and local features. Zanchettin, C. In Proceedings of the ACM Symposium on Applied Computing, 2014.
doi  abstract   bibtex   
This paper presents an evaluation of different methods considering the usually problems in face recognition. We consider variations in illumination, facial expression and facial details to propose a new method combining global and local face image features. This approach combines PCA, 2D-DCT and Gabor Wavelet Transform to obtain the global and local features representation. The Nearest Neighbor using the Euclidean distance performs the classification. The experiments were performed in the classical ORL and Yale face recognition databases. The proposed approach presented interesting results in comparison with the literature methods. Copyright 2014 ACM.
@inproceedings{
 title = {Face recognition based on global and local features},
 type = {inproceedings},
 year = {2014},
 keywords = {2D-DCT,Artificial neural nerworks,Gabor filters,Wavelets},
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 created = {2019-02-14T18:02:00.041Z},
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 abstract = {This paper presents an evaluation of different methods considering the usually problems in face recognition. We consider variations in illumination, facial expression and facial details to propose a new method combining global and local face image features. This approach combines PCA, 2D-DCT and Gabor Wavelet Transform to obtain the global and local features representation. The Nearest Neighbor using the Euclidean distance performs the classification. The experiments were performed in the classical ORL and Yale face recognition databases. The proposed approach presented interesting results in comparison with the literature methods. Copyright 2014 ACM.},
 bibtype = {inproceedings},
 author = {Zanchettin, C.},
 doi = {10.1145/2554850.2555078},
 booktitle = {Proceedings of the ACM Symposium on Applied Computing}
}

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