Detection and matching of facial marks in face images

Soft biometrics traits (e.g. gender, ethnicity, facial marks) are complementary information in face recognition. Although they are not fully distinctive by themselves, recent studies have proven that they can be combined with classical facial recognition techniques to increase the accuracy of the process. Facial marks, in particular, have proven useful in reducing the search for the identity of individuals, although they do not uniquely identify them. Facial marks based systems provide specic and more signicant evidence about the similarity between faces. In this paper we propose the use of facial marks (e.g. moles, freckles, warts) to improve the face recognition process. To that end, we implemented an algorithm for automatic detection of facial marks and we proposed two matching algorithms: one based on Histograms of Oriented Gradients (HoG) to represent the marks and the other based on the intensities of the pixels contained in each mark bounding box. Experimental results based on a set of 530 images (265 subjects) with manually annotated facial marks, show that the combination of traditional face recognition techniques with facial marks, increases the accuracy of the process.

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