Multi-scenario gesture recognition using Kinect

摘要

Hand gesture recognition (HGR) is an important research topic because some situations require silent communication with sign languages. Computational HGR systems assist silent communication, and help people learn a sign language. In this article, a novel method for contact-less HGR using Microsoft Kinect for Xbox is described, and a real-time HGR system is implemented. The system is able to detect the presence of gestures, to identify fingers, and to recognize the meanings of 18 gestures in two pre-defined gesture scenarios: Popular Gesture and the Numbers. The accuracy of the HGR system for Popular Gesture scenario is from 84% to 99% if a single hand performs the gestures, and from 90% to 100% if both hands perform the same gesture at the same time. The accuracy of the HGR system for the Numbers scenario is from 74% to 100% for single-hand gestures. Because the depth sensor of Kinect is an infrared camera, the lighting conditions, signers' skin colors and clothing, and background have little impact on the performance of this system. The accuracy and the robustness make this system a versatile component that can be integrated in a variety of applications in daily life.