Integrated Surface, Curve and Junction Inference from Sparse 3-D Data Sets

We areinterestedin descriptionsof 3-D data sets,as obtained from stereoor a 3-D digitizer. We thereforeconsideras inputa sparsesetof points, possibly associated with certain orientation information. In this paper, we address the problem of inferring integrated high-level descriptions such as surfaces, curves, and junctions from a sparse point set. While the method described in [5], [6] provides excellent results for smooth structures, it only detects discontinuities but does notlocalize them. Forpreciselocalization, we proposea non-iterative cooperativealgorithm in which surfaces, curves,and junctions work together: Initial estimates are computed based on [5], [6], whereeach point in the given sparse and possibly noisy point set is convolved with a predefinedvector mask to produce densesaliency maps. These maps serve as input to our novel maximal surface and curve marching algorithms for initial surface and curve extraction. Refinement of initial estimates is achieved by hybrid voting...

• Type: Conference
• Year: 1998
• Where: ICCV
• Authors: Chi-Keung Tang, Gérard G. Medioni
• Keywords: Certain Orientation Information, Computer Vision, Descriptionsof 3-D Data, ICCV 1998, Initial Estimates