Object and pose recognition with cellular genetic algorithms

Timo Mantere

doi:10.1117/12.733960

10 September 2007 Object and pose recognition with cellular genetic algorithms

Timo Mantere

Proceedings Volume 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision; 67640N (2007) https://doi.org/10.1117/12.733960
Event: Optics East, 2007, Boston, MA, United States

Abstract

We have studied the use of cellular automata and cellular genetic algorithms for the object recognition, pose recognition, and image classification problems. The cellular genetic algorithm is a genetic algorithm that has some similarities with cellular automata. The preliminary results seem to support the hypothesis that in principle this kind of object and pose recognition and image classification method works relatively well. The problem with the proposed method is a large amount of calculations needed when we are testing the unknown object against the objects in the comparison set.

Citation Download Citation

Timo Mantere "Object and pose recognition with cellular genetic algorithms", Proc. SPIE 6764, Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision, 67640N (10 September 2007); https://doi.org/10.1117/12.733960

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available