TY - GEN
T1 - Pareto optimal sensing strategies for an active vision system
AU - Dunn, Enrique
AU - Olague, Gustavo
AU - Lutton, Evelyne
AU - Schoenauer, Marc
PY - 2004
Y1 - 2004
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:4344635897
SN - 0780385152
SN - 9780780385153
T3 - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
SP - 457
EP - 463
BT - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
T2 - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
Y2 - 19 June 2004 through 23 June 2004
ER -