Hand gesture recognition using 3D sensors

The aim of this work is to investigate the problem of static hand gesture recognition using Kinect v2 depth sensor. We have dealt not only with the theory of recognition itself, but also with the use of depth sensors and the latest approaches in this field. We have successfully applied different convolutional neural network architectures to this classification problem and evaluated the impact of kernel size on the recognition score. By creating our own static gesture database, we have gained an objective way of comparing each test method.