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Tracking continuous topological changes of complex moving regions

Published: 21 March 2011 Publication History

Abstract

A moving region whose location and extend change over time can imply topological changes such as region split and hole formation. To study this phenomenon is useful in many applications, e.g. the topology control of wireless sensor networks and emergency handling. It is challenging to detect the topological changes of a moving region since we lack the ability to capture its continuous change of shapes all the time. Moreover, for a complex moving region containing multiple components, it is hard to determine which component before the change corresponds to which component after the change. In this paper, we propose a model to determine topological changes of a complex moving region through snapshots called observations. We introduce a two-phase strategy that the first phase partitions the observations into several evaluation units and uniquely maps a unit before the change to exactly one unit after the change; the second phase interprets the topological change by integrating all basic topological changes from evaluation units.

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  • (2023)Topological data analysis for geographical information science using persistent homologyInternational Journal of Geographical Information Science10.1080/13658816.2022.215565437:3(712-745)Online publication date: 4-Jan-2023
  • (2020)Removing uncertainty in neural networksCognitive Neurodynamics10.1007/s11571-020-09574-wOnline publication date: 27-Feb-2020
  • (2020)Suspicious Event Detection in Real-Time Video Surveillance SystemSocial Networking and Computational Intelligence10.1007/978-981-15-2071-6_40(509-516)Online publication date: 22-Mar-2020
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cover image ACM Conferences
SAC '11: Proceedings of the 2011 ACM Symposium on Applied Computing
March 2011
1868 pages
ISBN:9781450301138
DOI:10.1145/1982185
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 March 2011

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Author Tags

  1. complex region
  2. moving object
  3. topological change

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SAC'11
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SAC'11: The 2011 ACM Symposium on Applied Computing
March 21 - 24, 2011
TaiChung, Taiwan

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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The 40th ACM/SIGAPP Symposium on Applied Computing
March 31 - April 4, 2025
Catania , Italy

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Cited By

View all
  • (2023)Topological data analysis for geographical information science using persistent homologyInternational Journal of Geographical Information Science10.1080/13658816.2022.215565437:3(712-745)Online publication date: 4-Jan-2023
  • (2020)Removing uncertainty in neural networksCognitive Neurodynamics10.1007/s11571-020-09574-wOnline publication date: 27-Feb-2020
  • (2020)Suspicious Event Detection in Real-Time Video Surveillance SystemSocial Networking and Computational Intelligence10.1007/978-981-15-2071-6_40(509-516)Online publication date: 22-Mar-2020
  • (2019)Topology Based Object TrackingMathematical and Computational Applications10.3390/mca2403008424:3(84)Online publication date: 18-Sep-2019
  • (2018)Stability and Statistical Inferences in the Space of Topological Spatial RelationshipsIEEE Access10.1109/ACCESS.2018.28174936(18907-18919)Online publication date: 2018
  • (2017)Modelling Topological Features of Swarm Behaviour in Space and Time With Persistence LandscapesIEEE Access10.1109/ACCESS.2017.27493195(18534-18544)Online publication date: 2017
  • (2016)Trend-based prediction of spatial changeProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence10.5555/3060621.3060770(1074-1080)Online publication date: 9-Jul-2016
  • (2016)Representation of continuously changing data over time and space: Modeling the shape of spatiotemporal phenomena2016 IEEE 12th International Conference on e-Science (e-Science)10.1109/eScience.2016.7870891(111-119)Online publication date: Oct-2016
  • (2016)Compression of Spatio-temporal Data2016 17th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2016.80(4-7)Online publication date: Jun-2016
  • (2011)Decentralized reasoning about gradual changes of topological relationships between continuously evolving regionsProceedings of the 10th international conference on Spatial information theory10.5555/2040205.2040215(126-147)Online publication date: 12-Sep-2011
  • Show More Cited By

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