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Robust tracking of objects with dynamic topology

Corcoran, Padraig and Jones, Chris 2018. Robust tracking of objects with dynamic topology. Presented at: ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, Washington, USA, 6-9 November 2018. ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, pp. 428-431. 10.1145/3274895.3274922

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Abstract

In many instances of the object tracking problem the topological properties of objects can change over time. Such changes include the splitting of an object into multiple objects or merging of multiple objects into a single object. We propose a novel tracking model which is robust to such changes. This model is formulated terms of homology theory whereby 0-dimensional homology classes, which correspond to path-connected components, are tracked. A generalisation of this model for tracking spatially close objects lying in an ambient metric space is also proposed. This generalisation is particularly suitable for tracking spatial-temporal phenomena such as weather phenomena. The utility of the proposed model is demonstrated with respect to tracking rain clouds in radar imagery.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Additional Information: Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). SIGSPATIAL ’18, November 6–9, 2018, Seattle, WA, USA © 2018 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-5889-7/18/11. https://doi.org/10.1145/3274895.3274922
Publisher: ACM
ISBN: 978-1-4503-5889-7
Date of First Compliant Deposit: 27 November 2018
Date of Acceptance: 23 August 2018
Last Modified: 27 Nov 2018 11:45
URI: http://orca-mwe.cf.ac.uk/id/eprint/115581

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