Example-Based Object Detection in Images by Components
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulation optimization: a survey of simulation optimization techniques and procedures
Proceedings of the 32nd conference on Winter simulation
Video sequence segmentation using genetic algorithms
Pattern Recognition Letters
Guided Local Search — an Illustrative Example in Function Optimisation
BT Technology Journal
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
A neural network filter to detect small targets in high clutter backgrounds
IEEE Transactions on Neural Networks
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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.