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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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Contributor : Marc Schoenauer <>
Submitted on : Thursday, November 24, 2005 - 2:57:40 PM
Last modification on : Wednesday, March 27, 2019 - 4:41:29 PM


  • HAL Id : inria-00000845, version 1



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



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