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Human-Robot Interaction Based on Facial Expression Recognition Using Deep Learning

机译:基于使用深度学习的面部表情识别的人机交互

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In recent years, many robots for the purpose of communicating with people have been developed. Such a robot is required to have human interaction and communication ability. In order to perform the interaction naturally, the nonverbal communication such as human facial expression and body movement is important. In this research, we propose a method to classify emotions from human face images by deep learning and generate a robot emotional reaction by Markovian emotional model. Here, we perform to learn human facial images with various emotions using CNN (Convolutional Neural Network) which is a kind of deep learning, and recognize human emotions from facial images in the human interaction. Based on the human emotion obtained by deep learning, the robot returns its emotional behavior to the human. In this research, we executed the interaction experiment using an real communication robot and this result is also reported in this paper.
机译:近年来,许多机器人为了与人们沟通而开发。这种机器人需要具有人类的相互作用和通信能力。为了自然地进行相互作用,非语言通信如人的面部表情和身体运动是重要的。在这项研究中,我们提出了一种通过深受深入学习对人类脸部图像的情感进行分类的方法,并通过马尔可夫情绪模型产生机器人情绪反应。在这里,我们在使用CNN(卷积神经网络)的各种情绪中,我们表演学习人类面部图像,这些情绪是一种深入学习,并识别人类互动中的面部图像的人类情绪。基于深入学习获得的人类情感,机器人将其情绪行为归还给人类。在这项研究中,我们使用实际通信机器人执行了相互作用实验,并在本文中报告了该结果。

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