Title :
3D object identification based on matchings between a single image and a model
Author :
Pampagnin, L.H. ; Devy, M.
Abstract :
A model-based method for identifying convex or nonconvex polyhedral objects from a single image is described. An object is known by a region-edge-vertex model and an aspect graph. A few hypotheses are searched in a topological compatibility graph in which each node corresponds to a matching between chains of segments extracted from the image and model faces. The construction of this graph depends only on qualitative or topological criteria (number of edges for a face, syntactic description, perceptual organization, visibility, etc.). The search for hypotheses in the graph relies on the maximal cliques technique modified to deal with the global topological compatibility
Keywords :
graph theory; pattern recognition; topology; 3D object identification; convex polyhedral objects; graph theory; maximal cliques technique; model-based method; nonconvex polyhedral objects; pattern recognition; perceptual organization; region-edge-vertex model; segment chains matching; syntactic description; topological compatibility graph; Concurrent computing; Contracts; Image analysis; Image recognition; Image segmentation; Layout; Object recognition; Predictive models; Satellites; Two dimensional displays;
Conference_Titel :
Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on
Conference_Location :
Sacramento, CA
Print_ISBN :
0-8186-2163-X
DOI :
10.1109/ROBOT.1991.131843