Please use this identifier to cite or link to this item:
Title: Information assimilation framework for event detection in multimedia surveillance systems
Authors: Atrey, P.K.
Kankanhalli, M.S. 
Jain, R.
Keywords: Agreement coefficient
Compound and atomic events
Confidence fusion
Event detection
Information assimilation
Multimedia surveillance
Issue Date: 2006
Citation: Atrey, P.K., Kankanhalli, M.S., Jain, R. (2006). Information assimilation framework for event detection in multimedia surveillance systems. Multimedia Systems 12 (3) : 239-253. ScholarBank@NUS Repository.
Abstract: Most multimedia surveillance and monitoring systems nowadays utilize multiple types of sensors to detect events of interest as and when they occur in the environment. However, due to the asynchrony among and diversity of sensors, information assimilation - how to combine the information obtained from asynchronous and multifarious sources is an important and challenging research problem. In this paper, we propose a framework for information assimilation that addresses the issues - "when", "what" and "how" to assimilate the information obtained from different media sources in order to detect events in multimedia surveillance systems. The proposed framework adopts a hierarchical probabilistic assimilation approach to detect atomic and compound events. To detect an event, our framework uses not only the media streams available at the current instant but it also utilizes their two important properties - first, accumulated past history of whether they have been providing concurring or contradictory evidences, and - second, the system designer's confidence in them. The experimental results show the utility of the proposed framework. © Springer-Verlag 2006.
Source Title: Multimedia Systems
ISSN: 09424962
DOI: 10.1007/s00530-006-0063-8
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Mar 25, 2019


checked on Mar 6, 2019

Page view(s)

checked on Feb 2, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.