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Vision Based Body Dither Measurement for Estimating Human Emotion Parameters

机译:基于视觉的体型测量,用于估算人类情绪参数

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In this paper, we propose a new body dither analyzing method in order to estimating various kinds of intention and emotion of human. In previous researches for quantitatively measuring human intention and emotion, many kinds of physiological sensors such as ECG, PPG, GSR, SKT, and EEG have been adopted. However, these sensor based methods may supply inconvenience caused by sensor attachment to user. Also, therefrom caused negative emotion can be a noise factor in terms of measuring particular emotion. To solve these problems, we focus on facial dither by analyzing successive image frames captured from conventional webcam. For that, face region is firstly detected from the captured upper body image. Then, the amount of facial movement is calculated by subtracting adjacency two image frames. Since the calculated successive values of facial movement has the form of 1D temporal signal, all of conventional temporal signal processing methods can be used to analysis that. Results of feasibility test by inducing positive and negative emotions showed that more facial movement when inducing positive emotion was occurred compared with the case of negative emotion.
机译:在本文中,我们提出了一种新的身体抖动分析方法,以估计人类的各种意图和情感。在以前进行定量测量人类意图和情感的研究中,采用了多种生理传感器,如ECG,PPG,GSR,SKT和EEG。然而,这些基于传感器的方法可能为用户附件引起的不便提供给用户的不便。此外,由于测量特定的情绪,因此引起负面情绪可能是噪声因子。为了解决这些问题,我们通过分析从传统网络摄像机捕获的连续图像帧来专注于面部抖动。为此,首先从捕获的上半身图像检测面部区域。然后,通过减去邻接两个图像帧来计算面部移动的量。由于面部运动的计算的连续值具有1D时间信号的形式,因此所有传统的时间信号处理方法都可用于分析。通过诱导正面和负面情绪的可行性测试结果表明,与负面情绪的情况相比,发生了诱导积极情绪时的更多面部运动。

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