关键词: 交互式演化算法, 差分演化, 卡通人脸, 反向学习

Abstract: Components-based cartoon face generation is composed of components combination and features adjustment. These two stages can be solved through combination optimization and continuous optimization respectively. However, when cartoon face feature parameters are optimized, it is difficult to use functions to explicitly express the optimization objectives, which is a typical problem of implicit objective optimization. To solve this problem, this paper proposes the interactive differential evolution algorithm based on opposition-based learning strategy (IDE-OBL), which transforms the interaction method of artificially providing adaptive values by human beings in conventional interactive evolutionary algorithm to the method of pairwise comparison. In this new evolutionary algorithm, opposition-based learning strategies are applied to accelerate algorithm convergence, which will reduce the user evaluation times to some extent. The experimental results show that in cartoon face generation IDE-OBL is better than conventional IGA and IDE which do not use OBL, IDE-OBL reduces evolution iteration numbers and is beneficial for the ease of user fatigue.

Key words: interactive evolutionary algorithm, differential evolution, cartoon face, opposition-based learning