Development of an emotional gesture recognition system in dark environments

This paper presents an emotional gesture recognition system that is robust to dark illumination condition. This system employs a Kinect sensor to get a bright infrared image sequence in a dark environment and extract dense corner feature trajectories to capture spatio-temporal regions of interest. Furthermore, this system adopts bag-of-features (BOF) to represent a gesture and uses support vector machine (SVM) for gesture classification. The proposed system achieves 92.4% accuracy rate in a gesture dataset which is taken from the dark environment.