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Detecting Affect from Non-stylised Body Motions

机译:从非风格化的肢体动作检测影响

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摘要

In this paper we present a novel framework for analysing non-stylised motion in order to detect implicitly communicated affect. Our approach makes use of a segmentation technique which can divide complex motions into a set of automatically derived motion primitives. The parsed motion is then analysed in terms of dynamic features which are shown to encode affective information. In order to adapt our algorithm to personal movement idiosyncrasies we developed a new approach for deriving unbiased motion features. We have evaluated our approach using a comprehensive database of affectively performed motions. The results show that removing personal movement bias can have a significant benefit for automated affect recognition from body motion. The resulting recognition rate is similar to that of humans who took part in a comparable psychological experiment.
机译:在本文中,我们提出了一个新颖的框架来分析非风格化运动,以检测隐式传达的情感。我们的方法利用了一种分割技术,该技术可以将复杂的运动划分为一组自动派生的运动图元。然后根据动态特征对解析的运动进行分析,动态特征被显示为对情感信息进行编码。为了使我们的算法适应个人运动特质,我们开发了一种新的方法来推导无偏运动特征。我们使用情感执行动作的综合数据库评估了我们的方法。结果表明,消除个人运动偏向对于从身体运动中自动识别情感有很大的好处。最终的识别率与参加类似心理实验的人的识别率相似。

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