By Topic

Multimedia event-based video indexing using time intervals

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)
Snoek, C.G.M. ; Informatics Inst., Univ. of Amsterdam, Netherlands ; Worring, M.

We propose the time interval multimedia event (TIME) framework as a robust approach for classification of semantic events in multimodal video documents. The representation used in TIME extends the Allen temporal interval relations and allows for proper inclusion of context and synchronization of the heterogeneous information sources involved in multimodal video analysis. To demonstrate the viability of our approach, it was evaluated on the domains of soccer and news broadcasts. For automatic classification of semantic events, we compare three different machine learning techniques, i.c. C4.5 decision tree, maximum entropy, and support vector machine. The results show that semantic video indexing results significantly benefit from using the TIME framework.

Published in:

Multimedia, IEEE Transactions on  (Volume:7 ,  Issue: 4 )