Machine Vision and Applications

, Volume 11, Issue 3, pp 107–121

The model-based dynamic hand posture identification using genetic algorithm

  • Cheng-Chang Lien
  • Chung-Lin Huang

DOI: 10.1007/s001380050095

Cite this article as:
Lien, C. & Huang, C. Machine Vision and Applications (1999) 11: 107. doi:10.1007/s001380050095

Abstract.

This paper proposes a new hand posture identification system which applies genetic algorithm to develop an efficient 3D hand-model-fitting method. The 3D hand-model-fitting method consists of (1) finding the closed-form inverse kinematics solution, (2) defining the alignment measure function for the wrist-fitting process, and (3) applying genetic algorithm to develop the dynamic hand posture identification process. In contrast to the conventional computationally intensive hand-model-fitting methods, we develop an off-line training process to find the closed-form inverse kinematics solution functions, and a fast model-based hand posture identification process. In the experiments, we will illustrate that our hand posture identification system is very effective.

Key words:Inverse kinematics – Reach tree – Alignment measure – Genetic algorithm

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Cheng-Chang Lien
    • 1
  • Chung-Lin Huang
    • 2
  1. 1. Department of Computer Engineering, Chung-Hua University, Hsin-Chu, Taiwan, ROC; e-mail: cclien13@ms19.hinet.net TW
  2. 2. Department of Electrical Engineering, National Tsing-Hua University, Hsin-Chu, Taiwan, ROC; e-mail: clhuang@ee.nthu.edu.tw TW