Paper Info
Title
Real-time hand gesture recognition with Kinect for playing racing video games
Abstract
This paper presents a Kinect based hand gesture recognition system that can effectively recognize both one-hand and two-hand gestures. It is robust against the disturbance of complex background and objects such as the faces and hands of other people by exploiting the depth information and carefully choosing the region of interest (ROI) in the process of tracking. The recognition module is implemented using template matching and other light weight techniques to reduce the computational complexity. In the experiments, this system is tested on real world tasks from controlling the slide show in PowerPoint to playing the highly intense racing video game Need for Speed. The practical performance confirms that our system is both effective in terms of robustness and versatility and efficient for various real-time applications.
Year
DOI
Venue
2014
10.1109/IJCNN.2014.6889481
IJCNN
Keywords
Field
DocType
hand gesture recognition,Kinect,video games
Template matching,Computer vision,Computer science,Gesture,Gesture recognition,Robustness (computer science),Sketch recognition,Artificial intelligence,Region of interest,Computational complexity theory
Conference
ISSN
Citations 
PageRank 
2161-4393
12
0.74
References 
Authors
13
2
Name
Order
Citations
PageRank
Zhu Yanmin1120.74
Yuan Bo253247.01