Photogenic Expression Recognition using Gabor Filters and Support Vector Machines*
نویسندگان
چکیده
This paper presents a new view of the facial expression recognition problem, by addressing the question of whether or not is possible to classify previously labeled photogenic and non-photogenic face images, based on their appearance. In the proposed approach, a Support Vector Machine (SVM) is trained with Gabor representations of the face images to learn the relationships between facial expressions and the concept of a good photography of the face of a person. The obtained results showed that Gabor filters and SVM are promising, having presented good recognition rates.
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