EECS Department, The University of Toledo, Toledo, OH 43606, USA.
Sensors (Basel). 2018 Feb 1;18(2):416. doi: 10.3390/s18020416.
Extensive possibilities of applications have made emotion recognition ineluctable and challenging in the field of computer science. The use of non-verbal cues such as gestures, body movement, and facial expressions convey the feeling and the feedback to the user. This discipline of Human-Computer Interaction places reliance on the algorithmic robustness and the sensitivity of the sensor to ameliorate the recognition. Sensors play a significant role in accurate detection by providing a very high-quality input, hence increasing the efficiency and the reliability of the system. Automatic recognition of human emotions would help in teaching social intelligence in the machines. This paper presents a brief study of the various approaches and the techniques of emotion recognition. The survey covers a succinct review of the databases that are considered as data sets for algorithms detecting the emotions by facial expressions. Later, mixed reality device Microsoft HoloLens (MHL) is introduced for observing emotion recognition in Augmented Reality (AR). A brief introduction of its sensors, their application in emotion recognition and some preliminary results of emotion recognition using MHL are presented. The paper then concludes by comparing results of emotion recognition by the MHL and a regular webcam.
在计算机科学领域，情感识别的广泛应用使其成为必然且具有挑战性。非言语线索（如手势、身体动作和面部表情）的使用向用户传达了感觉和反馈。人机交互这一学科依赖于算法的稳健性和传感器的敏感性来改善识别。传感器通过提供高质量的输入在准确检测中发挥着重要作用，从而提高了系统的效率和可靠性。人类情绪的自动识别将有助于在机器中教授社交智能。本文对情感识别的各种方法和技术进行了简要研究。该调查涵盖了对数据库的简要回顾，这些数据库被视为通过面部表情检测情绪的算法的数据集。随后，引入了混合现实设备 Microsoft HoloLens (MHL) 来观察增强现实 (AR) 中的情感识别。简要介绍了其传感器、在情感识别中的应用以及使用 MHL 进行情感识别的一些初步结果。然后，本文通过比较 MHL 和常规网络摄像头的情感识别结果进行总结。
