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A data fusion system for object recognition based on transferable belief models and kalman filters

Powell, Gavin, Marshall, Andrew David, Milliken, Richard and Markham, Keith 2004. A data fusion system for object recognition based on transferable belief models and kalman filters. Presented at: Fusion2004, Stockholm, Sweden, 28 June- 1 July 2004. Published in: Svensson, Per and Schubert, Johan eds. Proceedings of the Seventh International Conference on Information Fusion. Mountain View, CA: International Society of Information Fusion (ISIF), pp. 54-61.

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Abstract

We examine the use of fusing data from multiple data sources for use within object recognition systems. We then continue, to illustrate the system that we have created for our own object recognition needs. The data fusion model that we use is embedded within an object recognition system that analyses simulated FLIR and LADAR data to recognise and track aircraft. The data fusion is based upon the Transferable Belief Model (TBM) and Kalman filters. The system is novel due to the simulation of the sensors and the use of multiple Kalman filters and TBM’s.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: TBM, fusion system, Kalman filter, ATR.
Publisher: International Society of Information Fusion (ISIF)
ISBN: 917056115X
Last Modified: 04 Jun 2017 04:44
URI: http://orca-mwe.cf.ac.uk/id/eprint/43901

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