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The point-descriptor-precedence representation for point configurations and movements / Amna Qayyum in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1374 - 1391 Titre : The point-descriptor-precedence representation for point configurations and movements Type de document : Article/Communication Auteurs : Amna Qayyum, Auteur ; Bernard De Baets, Auteur ; Muhammad Sulman Baig, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1374 - 1391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] courbe [Termes IGN] détection d'événement [Termes IGN] données spatiotemporelles [Termes IGN] mesurage de distances [Termes IGN] objet mobile [Termes IGN] reconnaissance de formes [Termes IGN] relation topologique [Termes IGN] trafic routier [Termes IGN] véhicule automobile Résumé : (auteur) In this paper, we represent (moving) point configurations along a curved directed line qualitatively by means of a system of relational symbols based on two distance descriptors: one representing distance along the curved directed line and the other representing signed orthogonal distance to the curved directed line. The curved directed line represents the direction of the movement of interest. For instance, it could be straight as in the case of driving along a highway or could be curved as in the case of an intersection or a roundabout. Inspired by the Point Calculus, the order between the points on the curved directed line is described by means of a small set of binary relations () acting upon the distance descriptors. We call this representation the Point-Descriptor-Precedence-Static (PDPS) representation at a time point and Point-Descriptor-Precedence-Dynamic (PDPD) representation during a time interval. To illustrate how the proposed approach can be used to represent and analyse curved movements, some basic micro-analysis traffic examples are studied. Finally, we discuss some extensions of our work to highlight the practical benefits of PDP in identifying motion patterns that could be useful in GIS, autonomous vehicles, sports analytics, and gait analysis. Numéro de notice : A2021-453 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1864378 Date de publication en ligne : 11/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1864378 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97882 [article]

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