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In this paper, we present a fully-automatic and real-time approach for person-independent recognition of facial expressions from dynamic sequences of 3D face scans. In the proposed solution, first a set of 3D facial landmarks are automatically detected, then the local characteristics of the face in the neighborhoods of the facial landmarks and their mutual distances are used to model the facial deformation...
Methods to recognize humans’ facial expressions have been proposed mainly focusing on 2D still images and videos. In this paper, the problem of person-independent facial expression recognition is addressed using the 3D geometry information extracted from the 3D shape of the face. To this end, a completely automatic approach is proposed that relies on identifying a set of facial keypoints, computing...
We investigate the problem of facial expression recognition using 3D face data. Our approach is based on local shape analysis of several relevant regions of a given face scan. These regions or patches from facial surfaces are extracted and represented by sets of closed curves. A Riemannian framework is used to derive the shape analysis of the extracted patches. The applied framework permits to calculate...
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