Stereo Analysis Using Individual Evolution Strategy

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ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Year:
2000

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Abstract

This paper presents an individual evolutionary strategy devised for image analysis applications. The example problem chosen is obstacle detection using a pair of cameras. The algorithm evolves a population of three-dimensional points ('flies') in the cameras fields of view, using a low complexity fitness function giving highest values to flies likely to be on the surfaces of 3-D obstacles. The algorithm uses classical sharing, mutation and crossover operators. The result is a fraction of the population rather than a single individual. Some test results are presented and potential extensions to real-time image sequence processing and mobile robotics are discussed.