Evolutionary Pose Measurement by Stereo Model Matching
Wei Song*, Yasushi Mae**, and Mamoru Minami**
*Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-0017, Japan
**Dept. of Human and Artificial Intelligent System, University of Fukui, 3-9-1 Bunkyo, Fukui 910-0017, Japan
Received:November 1, 2004Accepted:December 25, 2004Published:March 20, 2005
Keywords:pose measurement, genetic algorithm (GA), surface-strips model, Real-Time, visual servoing
This paper presents a pose measurement method of a 3-D object. The proposed method utilizes an evolutionary search technique of the genetic algorithm (GA) and a fitness evaluation based on a matching stereo model, named as surface-strips model here. The unprocessed gray-scale image, called a raw image, is used in order to perform recognition of a target using known target object shape. Here, the problem to recognize the position/orientation of the target object is converted to an optimization problem of a fitness function that consists in the computation of the brightness difference between an internal surface and a contour-strips. In order to evaluate the proposed 3-D recognition method, experiments to detect position/orientation of a rectangular solid block have been conducted to show its effectiveness of recognizing objects in static image. Furthermore, experiments to recognize a ball on a turning table by a robot manipulator equipped with two hand-eye cameras have also been conducted to show the effectiveness of this method for Real-Time visual servoing.
Cite this article as:W. Song, Y. Mae, and M. Minami, “Evolutionary Pose Measurement by Stereo Model Matching,” J. Adv. Comput. Intell. Intell. Inform., Vol.9 No.2, pp. 150-158, 2005.Data files: