Profile-based 3D-aided face recognition

This paper presents a framework for automatic face recognition based on a silhouetted face profile (URxD-PV). Previous research has demonstrated the high discriminative potential of this biometric. Compared to traditional approaches in profile-based recognition, our approach is not limited to only standard side-view faces. We propose to explore the feature space of profiles under various rotations with the aid of a 3D face model. In the enrollment mode, 3D data of subjects are acquired and used to create profiles under different rotations. The features extracted from these profiles are used to train a classifier. In the identification mode, the profile is extracted from the side-view image and its metadata is matched with the gallery metadata. We validate the accuracy of URxD-PV using data from publicly available databases.

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