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 978-1439856840Full text not available from this repository.
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|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited On:||08 Aug 2011 13:20|
|Last Modified:||30 Jan 2016 00:05|
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