By Topic

Gesture Analysis Using 3D Camera, Shape Features and Particle Filters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Gang Hu ; Fac. of Comput. Sci., Dalhousie Univ., Halifax, NS, Canada ; Qigang Gao

This paper presents a framework of gesture recognition and tracking using 3D camera, edge features and particle filters. A target gesture is modeled with perceptual shape features qualitatively. The perceptual model is used to guide tracking based on a particle filtering method to achieve reliable results. The system has been applied to a video game control application, Interactive Dart Game, where dart throwing gesture is modeled by learning from a training data set. The experiments are provided to demonstrate the proposed system which has a great potential for gesture analysis applications, such as sensor based video game and patient monitoring system.

Published in:

Computer and Robot Vision (CRV), 2011 Canadian Conference on

Date of Conference:

25-27 May 2011