BONSAI - 3-D OBJECT RECOGNITION USING CONSTRAINED SEARCH

Computer vision systems that identify and localize instances of predefined 3-D models in images offer many potential benefits to industrial and other environments. In many of these areas, solid models of the parts to be recognized already exist, and redesign of the part geometry for vision tasks should be avoided. This paper describes BONSAI, which is a model-based 3-D object recognition system, which identifies and localizes 3-D objects in range images of one or more parts that have been designed on a computer-aided design (CAD) system. Recognition is performed via constrained search of the interpretation tree, using unary and binary constraints (derived automatically from the CAD models) to prune the search space. We focus our attention on the recognition procedure, but we also outline the model-building, image acquisition, and segmentation procedures. Experiments with over 200 images demonstrate that the constrained search approach to 3-D object recognition has comparable accuracy to other existing systems.