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A mobile application to report and detect 3D body emotional poses

机译:报告和检测3D人体情感姿势的移动应用程序

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Most research into automatic emotion recognition is focused on facial expressions or physiological signals, while the exploitation of body postures has scarcely been explored, although they can be useful for emotion detection. This paper first explores a mechanism for self-reporting body postures with a novel easy to-use mobile application called EmoPose. The app detects emotional states from self-reported poses, classifying them into the six basic emotions proposed by Ekman and a neutral state. The poses identified by Schindler et al. have been used as a reference and the nearest neighbor algorithm used for the classification of poses. Finally, the accuracy in detecting emotions has been assessed by means of poses reported by a sample of users. (C) 2019 Elsevier Ltd. All rights reserved.
机译:对自动情感识别的大多数研究都集中在面部表情或生理信号上,尽管对人体姿势的检测可能很有用,但几乎没有研究对身体姿势的利用。本文首先探讨了一种利用名为EmoPose的易于使用的新颖移动应用程序自我报告身体姿势的机制。该应用程序从自我报告的姿势中检测出情绪状态,并将其分为Ekman提出的六种基本情绪和中立状态。辛德勒等人确定的姿势。已经用作参考,最近邻算法用于姿势分类。最后,已经通过用户样本报告的姿势评估了检测情绪的准确性。 (C)2019 Elsevier Ltd.保留所有权利。

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