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

A New Clustering Methodology for Group Photos Taken by Multiple Travelers

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)
Chuljin Jang ; Dept. of Comput. Sci. & Eng., Pusan Nat. Univ., Pusan, South Korea ; Taijin Yoon ; Hwan-Gue Cho

According to the popular use of digital camera, a traveler group carries multiple cameras for the same event. Previous studies on digital photo focused on massive unrelated photos or collections of a private user. But group travelers can carry several cameras and take photos simultaneously at the same time. Thus, an effective management for group photos is main issue for a traveler group. Since group photos from different photographers share their content, people need to collate the photos and classify them. We propose several supervised and unsupervised clustering methods for group photos. Previous studies are not applicable to group photos, because group photos do not guarantee clear relevance between photos which shown in private photo album. The proposed supervised clustering method, using spatio-temporal similarity, obtains a true cluster set of a specific camera from a user. It extracts discriminating features from given clusters and applies them to cluster other photos. Unsupervised methods use temporal photo blocks to compensate spatial variation of photos from a user. We use hierarchical clustering and neural network based clustering. In experiments, we show clustering results from real nomadic photo data. People can use a method suited to their needs.

Published in:

Computer and Information Technology, 2009. CIT '09. Ninth IEEE International Conference on  (Volume:1 )

Date of Conference:

11-14 Oct. 2009

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.