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We study the problem of classifying actions of human subjects using depth movies generated by Kinect or other depth sensors. Representing human body as dynamical skeletons, we study the evolution of their (skeletons’) shapes as trajectories on Kendall’s shape manifold. The action data is typically corrupted by large variability in execution rates within and across subjects and, thus, causing major...
This paper addresses the issue of Gender Classification from 3D facial images. While most of previous work in the literature focuses on either 2D facial images, here, we study the use of 3D facial shape for automatic gender classification. After a preprocessing step to extract the facial masks from triangular meshes obtained using laser range scanners, we approximate the facial surfaces by collections...
The 3D face recognition literature has many papers that represent facial shapes as collections of curves of different kinds (level-curves, iso-level curves, radial curves, profiles, geodesic polarization, iso-depth lines, iso-stripes, etc.). In contrast with the holistic approaches, the approaches that match faces based on whole surfaces, the curve-based parametrization allows local analysis of facial...
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