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Article dans une revue

Interactive trajectory modification and generation with FPCA

Abstract : Moving object analysis is a constantly growing field with numerous concrete applications in terms of traffic understanding, prediction and simulation. While many algorithms and analytic processes exist, there are still areas of investigation with novel trajectory analysis methods. As such, the geometric information analyses data with respect to its statistical distribution along extracted dimensions. This opens new ways of gaining a better understanding of large and complex trajectory data sets while providing flexible data manipulations. In this paper, we report our investigations with the development of an interactive methodology based on the geometric information analytic process where users can analyze trajectories sets, cluster and deform them maintaining the actual statistical properties of the investigated trajectories. As a contribution, this paper shows how Functional Data Analysis can provide novel support for trajectory analyses taking into account the statistical properties of the investigated clusters. We also provide recommendations for efficient usage of the process, considering trajectory registration, initial clustering, trajectory deformation and generation. These recommendations are illustrated with actual examples validated by a domain expert of air traffic flow analysis.
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Contributeur : daniel delahaye Connectez-vous pour contacter le contributeur
Soumis le : vendredi 6 mai 2022 - 09:45:21
Dernière modification le : jeudi 12 mai 2022 - 03:40:46
Archivage à long terme le : : dimanche 7 août 2022 - 18:12:54


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Gabriel Jarry, Almoctar Hassoumi, Daniel Delahaye, Christophe Hurter. Interactive trajectory modification and generation with FPCA. CEAS Aeronautical Journal, Springer, 2022, ⟨10.1007/s13272-022-00577-3⟩. ⟨hal-03660605⟩



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