Open/Closed Hand Classification Using Kinect Data

Abstract

This work proposes a study over five different hand gesture classifiers using depth and skeleton data from the Kinect sensor. Evaluations of sensibility, specificity and computational costs are performed for the purpose of choosing which methods are the most adequate. In spite of the low computational complexity of the tested classifiers, the results obtained are of similar quality compared to other complex approaches. All tested classifiers have been gathered in an open-source library for hand classification using the Kinect.