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—We present an accurate and robust framework for detecting and segmenting faces, localizing landmarks and achieving fine registration of face meshes based on the fitting of a facial model. This model is based on a 3D Point Distribution Model (PDM) that is fitted without relying on texture, pose or orientation information. Fitting is initialized using(More)
We present a novel approach to accurately detect landmarks and segment regions on face meshes without the use of texture, pose or orientation information. The proposed approach is based on a 3D Point Distribution Model (PDM) that is fitted to the region of interest using candidate vertices extracted from low-level feature maps. The robustness of the(More)
We present a novel approach to 3D face recognition using compact face signatures based on automatically detected 3D landmarks. We represent the face geometry with inter-landmark distances within selected regions of interest to achieve robustness to expression variations. The inter-landmark distances are compressed through Principal Component Analysis and(More)
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