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

A universal HMM-based approach to image sequence 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

2 Author(s)
Morguet, P. ; Inst. of Human-Machine-Commun, Munich Univ. of Technol., Germany ; Lang, M.

A universal approach to the classification of video image sequences by hidden Markov models (HMMs) is presented. The extraction of low level features allows the HMM to build an internal image representation using standard training algorithms. As a result, the states of the HMMs contain probability density functions, so called image density functions, which reflect the structure of the underlying images preserving their geometry. The successful application of the approach to both the recognition of dynamic head and hand gestures demonstrates the universal validity and sensitivity of our method. Even sequences containing only small detail changes are reliably recognized

Published in:

Image Processing, 1997. Proceedings., International Conference on  (Volume:3 )

Date of Conference:

26-29 Oct 1997

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.