Real-Time Embedded System for Gesture Recognition

Recognition from body movement is a challenging domain of research that lies at an intersection of machine learning, biometric security and cognitive functions domain. It can be highly beneficial for expert systems, lie detectors, border control, medical emergencies, as well as search and rescue operations. This paper describes a first prototype of a real-time system capable of recognizing four gestures that correlate to human emotions based on the arm movements. Features extracted from the 3D skeleton using Kinect v2 sensor are classified using an SVM method. The system is tested in real-time on a Kinect database with the embedded system using an optimized algorithm for skeleton extraction in real-time.