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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Robust Particle Filtering for Object Tracking
verfasst von : Daniel Rowe, Ignasi Rius, Jordi Gonzàlez, Juan J. Villanueva
Erschienen in: Image Analysis and Processing – ICIAP 2005
Verlag: Springer Berlin Heidelberg
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This paper addresses the filtering problem when no assumption about linearity or gaussianity is made on the involved density functions. This approach, widely known as
particle filtering
, has been explored by several previous algorithms, including
Condensation.
Although it represented a new paradigm and promising results have been achieved, it has several unpleasant behaviours. We highlight these misbehaviours and propose an algorithm which deals with them. A test-bed, which allows proof-testing of new approaches, has been developed. The proposal has been successfully tested using both synthetic and real sequences.