MULTIPLE VIEW GEOMETRY ESTIMATION BASED ON FINITE-MULTIPLE EVOLUTIONARY AGENTS FOR MEDICAL IMAGES

Mingxing Hu, Karen McMenemy, Stuart Ferguson, Gordon Dodds, Baozong Yuan

Abstract

In this paper we present a new method for the robust estimation of the trifocal tensor, from a series of medical images, using finite-multiple evolutionary agents. Each agent denotes a subset of matching points for parameter estimation, and the dataset of correspondences is considered as the environment in which the agents inhabit, evolve and execute some evolutionary behavior. Survival-of-finite-fitness rule is employed to keep the dramatic increase of new agents within limits, and reduce the chance of reproducing unfit ones. Experiments show that our approach performs better than the typical methods in terms of accuracy and speed, and is robust to noise and outliers even when a large number of outliers are involved.

References

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Paper Citation


in Harvard Style

Hu M., McMenemy K., Ferguson S., Dodds G. and Yuan B. (2005). MULTIPLE VIEW GEOMETRY ESTIMATION BASED ON FINITE-MULTIPLE EVOLUTIONARY AGENTS FOR MEDICAL IMAGES . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 972-8865-30-9, pages 202-209. DOI: 10.5220/0001169802020209


in Bibtex Style

@conference{icinco05,
author={Mingxing Hu and Karen McMenemy and Stuart Ferguson and Gordon Dodds and Baozong Yuan},
title={MULTIPLE VIEW GEOMETRY ESTIMATION BASED ON FINITE-MULTIPLE EVOLUTIONARY AGENTS FOR MEDICAL IMAGES},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2005},
pages={202-209},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001169802020209},
isbn={972-8865-30-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - MULTIPLE VIEW GEOMETRY ESTIMATION BASED ON FINITE-MULTIPLE EVOLUTIONARY AGENTS FOR MEDICAL IMAGES
SN - 972-8865-30-9
AU - Hu M.
AU - McMenemy K.
AU - Ferguson S.
AU - Dodds G.
AU - Yuan B.
PY - 2005
SP - 202
EP - 209
DO - 10.5220/0001169802020209