Moving parabolic approximation of point clouds
Computer-Aided Design
Self-organizing approach to moving surface reconstruction
ISCGAV'09 Proceedings of the 9th WSEAS international conference on Signal processing, computational geometry and artificial vision
3D geometry from uncalibrated images
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
3D shape from unorganized 3d point clouds
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
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We present a new method for defining neighborhoods, and assigning principal curvature frames, and mean and Gauss curvatures to the points of an unorganized oriented point-cloud. The neighborhoods are estimated by measuring implicitly the surface distance between points. The 3D shape recovery is based on conformal geometry, works directly on the cloud, does not rely on the generation of polygonal, or smooth models. Test results on publicly available synthetic data, as ground truth, demonstrate that the method compares favorably to the established approaches for quantitative 3D shape recovery. The proposed method is developed to serve applications involving point based rendering and reliable extraction of differential properties from noisy unorganized point-clouds.