We describe an effective and novel approach to infer sign and direction of principal curvatures at each input site from noisy 3D data. Unlike most previous approaches, no local su...
We address the problem of unsupervised segmentation and grouping in 2D and 3D space, where samples are corrupted by noise, and in the presence of outliers. The problem has attract...
We are interested in feature extraction from volume data in terms of coherent surfaces and 3-D space curves. The input can be an inaccurate scalar or vector field, sampled densely...
We areinterestedin descriptionsof 3-D data sets,as obtained from stereoor a 3-D digitizer. We thereforeconsideras inputa sparsesetof points, possibly associated with certain orien...