The main task of traffic monitoring applications is to identify moving targets. Usually, these applications require that a large number of parameters is tuned in order to work properly. In the motion detection system we have developed, about thirty parameters have been required to be optimized. This paper shows how a distributed implementation of a Genetic Algorithm (GA) over a network of workstations can successfully accomplish the parameter optimization task within a reduced amount of time. Accurate experiments accomplished on a challenging training sequence yield optimal parameter values. Four more test sequences allow us to assess the generality of the results previously attained.
A. Bevilacqua (2005). Optimizing parameters of a motion detection system by means of a distributed genetic algorithm. IMAGE AND VISION COMPUTING, 23:9, 815-829 [10.1016/j.imavis.2005.04.001].
Optimizing parameters of a motion detection system by means of a distributed genetic algorithm
BEVILACQUA, ALESSANDRO
2005
Abstract
The main task of traffic monitoring applications is to identify moving targets. Usually, these applications require that a large number of parameters is tuned in order to work properly. In the motion detection system we have developed, about thirty parameters have been required to be optimized. This paper shows how a distributed implementation of a Genetic Algorithm (GA) over a network of workstations can successfully accomplish the parameter optimization task within a reduced amount of time. Accurate experiments accomplished on a challenging training sequence yield optimal parameter values. Four more test sequences allow us to assess the generality of the results previously attained.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
