Abstract
Expression recognition via facial and corporal movements plays an important role in our daily lives. In this paper, a new method for expression recognition is proposed. We collected a bi-modal dataset of facial and corporal expressions of 9 subjects performance of six expressions (sadness, surprise, happiness, fear, anger, and neutral) using Kinect (v1) and Kinect (v2). New geometrical features including a combination of angle and distance features are used to train multiple classifiers. This work concentrates on facial and corporal expression and feature extraction. For system performance assessment, we used leave-one-out subject cross-validation. The obtained results show the superior performance of the RGB-D features provided by Kinect (v2).
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