By Topic

Event Detection Based on Hierarchical Event Fusion

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)
Xiaoling Xiao ; Sch. of Comput. Sci., Yangtze Univ., Jingzhou, China ; Xiang Zhang

This paper proposes a method for event detection based on hierarchical event fusion. Four high-level events in intelligent meeting scenarios, namely, ldquomonologuerdquo,ldquopresentationrdquo, ldquodiscussionrdquo, and ldquobreakrdquo, are analyzed. To characterize these four events by hierarchical event fusion and inference, four kinds of group events are considered. Group events are analyzed based on three kinds of basic states of individual participants, such as location, standing or sitting, and speaking or silence. Rao-Blackwellized particle filters are applied to make event inference in real time. The experimental results indicate that this approach is effective in detecting high-level event.

Published in:

Environmental Science and Information Application Technology, 2009. ESIAT 2009. International Conference on  (Volume:2 )

Date of Conference:

4-5 July 2009