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首页> 外文会议>IEEE International symposium on computer-based medical systems >Generating Facial Emotions for Diagnosis and Training
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Generating Facial Emotions for Diagnosis and Training

机译：产生面部情绪以进行诊断和训练

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摘要

The ability to process and identify facial emotions is an essential factor for an individuals social interaction. There are certain psychiatric disorders that can limit an individuals ability to recognize emotions in facial expressions. This problem could be confronted by making use of computational techniques in order to develop learning environments for the diagnosis, evaluation and training in identifying facial emotions. This paper presents an approach that uses image processing techniques, formal languages, anthropometry and Facial Action Coding System (FACS) to generate caricatures that represent facial movements related to neutral, satisfaction, sadness, anger, disgust, fear and surprise emotions. The rules that define the emotions were determined using an AND-OR graph to enable generating these images in a flexible manner. An evaluation conducted with healthy volunteers showed that some emotions are more easily recognized, while for other emotions the caricatures need to be further improved. This is a promising approach, since the parameters used provide flexibility to define the emotional intensity that must be represented.
机译：处理和识别面部表情的能力是个人社交互动的重要因素。有些精神病会限制个人识别面部表情中情绪的能力。为了发展用于诊断，评估和训练面部表情的学习环境，可以通过使用计算技术来解决这个问题。本文提出了一种使用图像处理技术，形式语言，人体测量学和面部动作编码系统（FACS）来生成代表与中立，满意，悲伤，愤怒，厌恶，恐惧和惊奇情绪有关的面部动作的漫画的方法。使用AND-OR图确定定义情感的规则，以便能够灵活地生成这些图像。与健康志愿者进行的评估表明，某些情绪更容易被识别，而对于其他情绪，漫画的表达需要进一步改善。这是一种很有前途的方法，因为所使用的参数提供了定义必须表达的情绪强度的灵活性。

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