Abstract
In this paper we introduce a novel sensor fusion algorithm based on the cooperative coevolutionary paradigm. We develop a multisensor robust moving object detection system that can operate under a variety of illumination and environmental conditions. Our experiments indicate that this evolutionary paradigm is well suited as a sensor fusion model for different sensing modalities.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Nadimi, S., Bhanu, B.: Multistrategy fusion using mixture model for moving object detection. In: Intl. Conf. Multisensor Fusion & Integration for Intelligent Systems, pp. 317–322 (2001)
Potter, M.A., De Jong, K.A.: Cooperative coevolution: an architecture for evolving coadapted subcomponents. Evolutionray Computation 8(1), 1–29 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nadimi, S., Bhanu, B. (2004). Cooperative Coevolution Fusion for Moving Object Detection. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_61
Download citation
DOI: https://doi.org/10.1007/978-3-540-24854-5_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22344-3
Online ISBN: 978-3-540-24854-5
eBook Packages: Springer Book Archive