By Topic

System architecture and techniques for gesture recognition in unconstrained environments

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

1 Author(s)
M. R. J. Kohler ; Dortmund Univ., Germany

Controlling appliances in home environments by gestures is a step towards more intuitive and natural human computer interfaces. A brief overview of an existing vision based gesture recognition system and its architecture and details of ergonomic remote control of devices by gestures are clarified. The focus is on motion detection, object normalization and identification, modelling, and prediction of motion using a Kalman filter. The initialization problem of the Kalman filter of a vision based system for human motion tracking differs from initialization for physical systems, where manuals report measurement errors. One main aim was to develop the initialization and adequate Kalman model for human motion. Most aspects mentioned in the report were implemented in the ARGUS prototype

Published in:

Virtual Systems and MultiMedia, 1997. VSMM '97. Proceedings., International Conference on

Date of Conference:

10-12 Sep 1997