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Sensor and Data Fusion:Taxonomy, Challenges and Applications

Klein, Lawrence and Mihaylova, Lyudmila and El Faouzi, Nour-Eddin (2012) Sensor and Data Fusion:Taxonomy, Challenges and Applications. In: Handbook on Soft Computing for Video Surveillance. Chapman & Hall, USA, pp. 139-183. ISBN 978-1439856840

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Abstract

Sensor and data fusion is a process of paramount importance for many domains and applications. Its potential for rapid data and information processing are of primary importance for surveillance, security, intelligent transportation systems, navigation and communications. Effective use of the data requires the sensor and context data to be aggregated or “fused” in such a way that high quality information results and serves as a basis for decision support. Data fusion encompasses groups of methods for merging various types of data and information. This process is especially important for tracking systems. This chapter presents taxonomy of sensor data fusion methods. Applications from object tracking in video are presented.

Item Type: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: sensor data fusion ; Taxonomy ; tracking ; Bayesian inference ; video
Subjects: UNSPECIFIED
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 49440
Deposited By: ep_importer_pure
Deposited On: 08 Aug 2011 13:20
Refereed?: No
Published?: Published
Last Modified: 10 Apr 2014 00:36
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/49440

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