Cart (Loading....) | Create Account
Close category search window
 

A robust Bayesian network for articulated motion classification

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
$31 $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

3 Author(s)
Imennov, N.S. ; Dept. of Comp. Sci. & Biomedical Eng., Rochester Univ., NY, USA ; Dockstader, S.L. ; Tekalp, A.M.

We introduce a new approach to motion-based recognition that combines the temporally descriptive abilities of a hidden Markov model (HMM) with the inferential power of a Bayesian belief network. We define activities using a collection of multiple Markov models, each associated with a unique set of body model parameters or gait variables. A single Bayesian network integrates the models by operating on virtual evidence derived from the HMM conditional output probabilities. We introduce both fundamental and auxiliary models for characterizing events and tracking failures, respectively. We demonstrate the system using multi-view video sequences corrupted by occlusion, noise, and entirely missing observations.

Published in:

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on  (Volume:3 )

Date of Conference:

14-17 Sept. 2003

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.