Retrieval system to generate facial expressions using chaos

T. Sato, P. Ushida, T. Yamaguchi
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引用次数: 1

Abstract

An image generation method is introduced that provides creativity support for image generation. This method is driven by chaotic dynamics, employing a facial expression model constructed on fuzzy associative memories. User's creativity support regarding expressions is provided by clarifying the image through repetition of the following procedures. First, a user is shown a facial expression candidate by chaotic retrieval from a fuzzy associative memory network. The user then selects an appropriate candidate and changes the external input to the network. Computer simulation results for actual facial expression data show that this method is an effective creativity support. A leaning method is also described, in which facial expressions obtained from creativity support are memorized in the facial expression model.<>
利用混沌生成面部表情的检索系统
介绍了一种为图像生成提供创造性支持的图像生成方法。该方法由混沌动力学驱动,采用基于模糊联想记忆的面部表情模型。用户在表达方面的创造力支持是通过重复以下步骤来澄清图像。首先,通过模糊联想记忆网络的混沌检索向用户显示候选面部表情。然后,用户选择一个合适的候选者,并更改网络的外部输入。对实际面部表情数据的计算机仿真结果表明,该方法是一种有效的创造力支持方法。本文还描述了一种学习方法,将从创造力支持中获得的面部表情记忆到面部表情模型中
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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