A hierarchical structure for gesture recognition using RGB-D sensor

Abstract

Recently, gesture recognition using visual sensors has been paid increased attention as an intelligent technology for human-computer interaction. To achieve good recognition performance in vision-based gesture recognition, it is important to find an efficient representation of complex visual signals and a robust classification method that can deal with diverse variations of gesture data. To treat these challenging topics, we propose a hierarchical structure for feature extraction and measuring similarity between two gestures obtained through RGB-D video sensors such as Kinect. The efficiency of the proposed method is confirmed through computational experiments on a public benchmark database.