Real-time Body Gestures Recognition using Training Set Constrained Reduction
- Authors: Milazzo, F.; Gentile, V.; Sorce, S.; Gentile, A.
- Publication year: 2017
- Type: Contributo in atti di convegno pubblicato in volume
- OA Link: http://hdl.handle.net/10447/229282
Abstract
Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition accuracy, the required time for recognition can be dramatically reduced.