Development of advanced evolutionary computation methods for complex structure and their applications to motion picture processing

点击翻译按钮获取中文摘要

We studied to develop new evolutionary computation algorithms for complex structures including tree structures with several numerical parameters, network structures, graph structures and so on. Conventional evolutionary algorithms such as GA (Genetic Algorithm) and GP (Genetic Programming) cannot optimize such complex structures.We developed three kinds algorithms for them.First, we developed an algorithm named "GMA (Genetic Matrix Algorithm)" for optimization of tree structures with several numerical parameters and applied it to automatic construction of image processing methods.Second, we constructed GIN (Genetic Image Network) for optimization of network structures whose node is an image filter, and we showed that GIN can generate automatically complex image processing procedures.Third, we developed GRAPE (GRAph structured Program Evolution) for automatic programming. GRAPE can generate general programs based on machine learning of learning data. For instance, GRAPE can make sorting programs from examples of several original data and their correctly sorted data.We applied the above methods to automatic generation of image processing algorithms especially motion picture processing such as extraction of human and automobile regions form motion pictures. We can generate complex image processing algorithms very easily using the developed evolutionary algorithms. These methods can be applied to various kinds of fields.