Occluded face recognition based on Gabor wavelets

Kepenekci, B
Tek, FB
Akar, Gözde
A new feature based approach to frontal face recognition with Gabor wavelets is presented in this paper. The feature points are automatically extracted using the local characteristics of each individual face in order to decrease the effect of occluded features. There is no training as in neural network approaches, thus single frontal face for each individual is enough as reference. Experimental results show that the proposed method achieves a recognition ratio of over %95.


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Kepenekci, B; Akar, Gözde (2004-04-30)
A new approach to feature based frontal face recognition with Gabor wavelets and support vector machines is presented in this paper. The feature points are automatically extracted using the local characteristics of each individual face. A kernel that computes the similarity between two feature vectors, is used to map the face features to a space with higher dimension. To find the identity of a test face, the possible labels of each feature vector of that face is found with support vector machines, then the ...
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Citation Formats
B. Kepenekci, F. Tek, and G. Akar, “Occluded face recognition based on Gabor wavelets,” 2002, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53282.