3-D object recognition using a genetic algorithm-based search scheme

The main difficulty in recognizing 3-D objects from 2-D images is matching 2-D information to the 3-D object representation. The multiple-view approach makes this problem easy to solve by reducing the problem to 2-D to 2-D matching problem. This approach models each 3-D object by a collection of 2-D views from various viewing angles and recognizes an object in the image by finding a 2-D view that has the best match to the image. However, if the size of the model database becomes large, the approach requires long time for the recognition of objects. In this paper we present a 3-D object recognition algorithm based on multiple-view approach. To reduce the recognition time, the proposed algorithm uses the coarse-to-fine process previously proposed by the authors [19] and a genetic algorithm-based search scheme for the selection of a best matched model in the database. And, we could verify from the results of the experiments that the algorithm proposed in this paper is useful to speed up the recognition process in multiple-view based object recognition systems.