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Integrating shape and dynamic probabilistic models for data association and tracking | IEEE Conference Publication | IEEE Xplore

Integrating shape and dynamic probabilistic models for data association and tracking


Abstract:

Tracking and data association procedures like the joint probabilistic data association filter (JPDAF) are not prone to the integration of additional information, such as ...Show More

Abstract:

Tracking and data association procedures like the joint probabilistic data association filter (JPDAF) are not prone to the integration of additional information, such as shape constraints. A standard probabilistic framework is not suited to merging partially incoherent information sources. The theory of evidence, introduced by Shafer, describes a way to combine distinct "bodies of evidence" about the same phenomena. Under this framework we provide a rigorous derivation of the JPDAF as well as a procedure to integrate additional shape knowledge.
Date of Conference: 10-13 December 2002
Date Added to IEEE Xplore: 10 March 2003
Print ISBN:0-7803-7516-5
Print ISSN: 0191-2216
Conference Location: Las Vegas, NV, USA

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