Object modeling from multiple images using genetic algorithms

Abstract

This paper describes an application of genetic algorithms (GAs) to modeling of multiple objects from CCD images. Shape modeling is a very important issue for shape recognition for robot vision, representing 3-D shapes in the virtual world, and so on. In this paper, we propose a method for object modeling from multiple view images using genetic algorithms (GAs). In this method, similarity between the model and the image at each view angle is evaluated. The model having the maximum evaluation is found by GAs. In the proposed method, a sharing scheme is used for finding multiple solutions efficiently. Some results of object modeling experiments from synthetic and real multiple view images demonstrate that the proposed method can robustly generate models by using GAs.