Pareto optimal sensing strategies for an active vision system

Enrique Dunn, Gustavo Olague, Evelyne Lutton, Marc Schoenauer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

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 fixed 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 flexibility and effectiveness of our approach and offer new research alternatives in the field of sensor planning.

Original languageEnglish
Title of host publicationProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Pages457-463
Number of pages7
StatePublished - 2004
EventProceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States
Duration: 19 Jun 200423 Jun 2004

Publication series

NameProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Volume1

Conference

ConferenceProceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Country/TerritoryUnited States
CityPortland, OR
Period19/06/0423/06/04

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