Obtaining a polyhedral model by integration of multiview images via genetic algorithms

Hideo Saito; Satoshi Kirihara

doi:10.1117/12.294456

10 December 1997 Obtaining a polyhedral model by integration of multiview images via genetic algorithms

Hideo Saito, Satoshi Kirihara

Proceedings Volume 3204, Three-Dimensional Imaging and Laser-based Systems for Metrology and Inspection III; (1997) https://doi.org/10.1117/12.294456
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States

Abstract

Shape modeling is a very important issue for many studies, for example, object recognition for robot vision, virtual environment construction, and so on. In this paper, a new method for obtaining polyhedral model from multiview images using genetic algorithms (GAs) is proposed. In this method, a similarity between model and every input image is calculated, and then the model which has the maximum similarity is found. For finding the model of maximum similarity, genetic algorithms are used as the optimization method. In the genetic algorithm, the sharing scheme is employed for efficient detection of multiple solution, because some shape may be represented by multiple shape models. Some results of modeling experiments from real multiple images demonstrate that the proposed method can robustly generate model by using the GA.

Citation Download Citation

Hideo Saito and Satoshi Kirihara "Obtaining a polyhedral model by integration of multiview images via genetic algorithms", Proc. SPIE 3204, Three-Dimensional Imaging and Laser-based Systems for Metrology and Inspection III, (10 December 1997); https://doi.org/10.1117/12.294456

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