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

Periodic motion detection with ROI-based similarity measure and extrema-based reference selection

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

4 Author(s)
Gaojian Li ; Sch. of Comput. Sci. & Technol., Fudan Univ., Shanghai, China ; Xintong Han ; Weiyao Lin ; Hui Wei

This paper presents a new algorithm for detecting and analyzing the periodic motions in video sequences. Different from the previous methods which detect periodic motions from the entire frame, we propose a convexhull- based process to automatically determine the regions of interest (ROI) of the motions and utilize an ROI-based similarity measure to detect the motion periods. Furthermore, we also propose an extrema-based method to select the optimal reference frame for further improving the periodic detection performance. Our proposed algorithm can not only effectively detect motion periods with both constant and variable period lengths, but also have obvious advantage when handling periodic motion with slight movements. Experimental results demonstrate the effectiveness of our proposed method.

Published in:

Consumer Electronics, IEEE Transactions on  (Volume:58 ,  Issue: 3 )

Date of Publication:

August 2012

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.