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Towards Recognizing Emotion with Affective Dimensions Through Body Gestures

机译:通过身体姿势识别情感维度的情感

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Due to the ever-increasing importance of computers in many areas of today’s society such as e-Learning, tele home-health care, and entertainment, their ability to interact well with humans is essential. Currently, researchers are using facial expression and voice recognition modalities to create systems that interact with humans. But still two problems exist: gesture is not yet a concern as a channel of affective communication in interactive technology, and existing systems only model discrete categories but not affective dimensions, e.g., intensity. Our focus has been on creating affective gesture recognition system that recognize child’s emotion with intensity through body gestures in context of game. This information is then used by a Game control module that users a rule-based adaptation model to change game level according to the child’s intensity of emotions. Results show that affective gesture recognition model recognized child’s emotion over 79% of the cases and the proposed intensity estimate model has a strong relationship with observer perception except in the low intensity level.
机译:由于计算机在当今社会的许多领域(例如,电子学习,远程家庭保健和娱乐)中日益重要的地位,因此它们与人之间良好交互的能力至关重要。当前,研究人员正在使用面部表情和语音识别方式来创建与人类互动的系统。但是仍然存在两个问题:作为交互技术中的情感交流的渠道,手势尚未引起关注,并且现有系统仅对离散类别建模,而对情感维度(例如强度)不建模。我们一直致力于创建情感手势识别系统,该系统可以通过游戏中的肢体手势来识别孩子的情绪。然后,游戏控制模块会使用此信息,该模块会使用基于规则的适应模型来根据孩子的情绪强度来更改游戏级别。结果表明,情感手势识别模型可以识别超过79%的情况下的孩子的情绪,并且所提出的强度估计模型与观察者的知觉有很强的关系,但强度强度水平较低。

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