Recognizing Emotions Conveyed by Human Gait
Recognizing Emotions Conveyed by Human Gait
复制标题
识别人类步态传达的情绪
DOI：
10.1007/s12369-014-0243-1
复制
发表时间：
2014
影响因子：
4.7
通讯作者：
Halim Hicheur
中科院分区：
文献类型：
--
作者：
G. Venture;H. Kadone;Tianxiang Zhang;J. Grèzes;A. Berthoz;Halim Hicheur
人类通过不同的方式表达情感。步态就是其中之一。在这里，我们建议使用步态数据来突出特征的情绪。步态分析的研究主要集中在站姿、频率、步长等方面。在这里，该研究是基于从反向运动学计算获得的关节角度，该反向运动学计算使用从标记3D位置的反向运动学获得的34DOF人体模型的自由度（DOF）的组合从3D运动捕获数据获得。候选人是四位专业演员，模拟了五种情绪状态：中性，喜悦，愤怒，悲伤和恐惧。本文首先提出了一种心理学方法，其结果被用来提出数值方法。第一项研究提供了32名观察者关于运动感知和从步态识别情绪的可能性的心理学结果。然后，运动数据的研究，使用特征向量的方法来验证的情感的数值可识别性。最后，针对参考运动的数据库测试每个运动以识别所传达的情感。使用第一和第二研究结果，我们使用6DOF模型，然后使用12DOF模型。实验结果表明，通过使用步态特征，它是可能的，以良好的准确性为主题内的数据库中的每一种情绪。对于跨学科数据库的结果表明，识别更容易出错，这表明强烈的人际情感特征的差异。
Humans convey emotions through different ways. Gait is one of them. Here we propose to use gait data to highlight features that characterize emotions. Gait analysis study usually focuses on stance phase, frequency, footstep length. Here the study is based on the joint angles obtained from inverse kinematics computation from the 3D motion-capture data using a combination of degrees of freedom (DOF) out of a 34DOF human body model obtained from inverse kinematics of markers 3D position. The candidates are four professional actors, and five emotional states are simulated: Neutral, Joy, Anger, Sadness, and Fear. The paper presents first a psychological approach which results are used to propose numerical approaches. The first study provides psychological results on motion perception and the possibility of emotion recognition from gait by 32 observers. Then, the motion data is studied using a feature vector approach to verify the numerical identifiability of the emotions. Finally each motion is tested against a database of reference motions to identify the conveyed emotion. Using the first and second study results, we utilize a 6DOF model then a 12DOF model. The experimental results show that by using the gait characteristics it is possible to characterize each emotion with good accuracy for intra-subject data-base. For inter-subject database results show that recognition is more prone to error, suggesting strong inter-personal differences in emotional features.
影响因子：
24.8
作者：
Izard CE
通讯作者：
Izard CE