Title :
Multi-scenario gesture recognition using Kinect
Author_Institution :
Comput. Eng. & Comput. Sci., Univ. of Louisville, Louisville, KY, USA
fDate :
July 30 2012-Aug. 1 2012
Abstract :
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.
Keywords :
cameras; gesture recognition; human computer interaction; image colour analysis; infrared detectors; learning (artificial intelligence); real-time systems; Kinect depth sensor; Microsoft Kinect; Xbox; both hand gesture recognition; computational HGR systems; contact-less HGR; infrared camera; lighting conditions; multiscenario gesture recognition; number gesture scenario; popular gesture scenario; real-time HGR system; sign language learning; signer clothing; signer skin colors; silent communication; single hand gesture recognition; Accuracy; Cameras; Gesture recognition; Handicapped aids; Thumb; Vectors; Human-computer interaction; Kinect; finger identification; hand gesture recognition;
Conference_Titel :
Computer Games (CGAMES), 2012 17th International Conference on
Conference_Location :
Louisville, KY
Print_ISBN :
978-1-4673-1120-5
DOI :
10.1109/CGames.2012.6314563