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Conference Papers Year : 2004

Pareto Optimal Sensing Strategies for an Active Vision System

Abstract

We present a multi-objective methodology, based on evolutionary computation, for solving the sensor planning problem for an active vision system. The application of different representation schemes, that allow to consider either xed or variable size camera networks in a single evolutionary process, is studied. Furthermore, a novel representation of the recombination and mutation operators is brought forth. The developed methodology is incorporated into a 3D simulation environment and experimental results shown. Results validate the exibility and effectiveness of our approach and offer new research alternatives in the eld of sensor planning.
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Dates and versions

inria-00000845 , version 1 (23-11-2020)

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  • HAL Id : inria-00000845 , version 1

Cite

Enrique Dunn, Gustavo Olague, Evelyne Lutton, Marc Schoenauer. Pareto Optimal Sensing Strategies for an Active Vision System. CEC 2004, Jun 2004, Portland, United States. ⟨inria-00000845⟩
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