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Spatial knowledge acquisition with virtual semantic landmarks in mixed reality-based indoor navigation / Bing Liu in Cartography and Geographic Information Science, vol 48 n° 4 (July 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 4 (July 2021) . - pp 305 - 319 Titre : Spatial knowledge acquisition with virtual semantic landmarks in mixed reality-based indoor navigation Type de document : Article/Communication Auteurs : Bing Liu, Auteur ; Linfang Ding, Auteur ; Liqiu Meng, Auteur Année de publication : 2021 Article en page(s) : pp 305 - 319 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] conception orientée utilisateur [Termes IGN] GPS assisté pour la navigation (technologies) [Termes IGN] hologramme [Termes IGN] information sémantique [Termes IGN] navigation virtuelle [Termes IGN] point de repère [Termes IGN] positionnement en intérieur [Termes IGN] questionnaire [Termes IGN] réalité mixte [Termes IGN] téléphone intelligent [Termes IGN] utilisateur civil Résumé : (auteur) Landmarks are essential and widely used in human navigation. However, many indoor environments lack visually salient landmarks, which leads to difficulties in navigating in and learning complex and similar-looking indoor environments. In this study, we designed and implemented virtual semantic landmarks in Mixed Reality (MR)-based indoor environments and conducted a user study to explore whether such landmarks can assist spatial knowledge acquisition during navigation. More specifically, we employed the untethered, head-mounted mixed reality device Microsoft HoloLens and used iconic holograms to show the semantic landmarks. In the user study, we used sketch map, landmark locating tasks and interview to assess the results of the spatial knowledge acquisition and collect advice on improving the MR-based navigation interface. The results show that virtual semantic landmarks can assist the acquisition of corresponding knowledge, as such landmarks were labeled second most often in landmark locating task. In addition, individual cases show that head-mounted mixed reality devices may influence not only vision, but also height or time perception of certain users. Our result can be applied to facilitate the design of MR-based navigation interfaces and assist spatial knowledge acquisition. Numéro de notice : A2021-445 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1908171 date de publication en ligne : 22/04/2021 En ligne : https://doi.org/10.1080/15230406.2021.1908171 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97852 [article]

Stop-and-move sequence expressions over semantic trajectories / Yenier Torres Izquierdo in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 4 (April 2021) . - pp 793 - 818 Titre : Stop-and-move sequence expressions over semantic trajectories Type de document : Article/Communication Auteurs : Yenier Torres Izquierdo, Auteur ; Grettel Monteagudo Garcia, Auteur ; Marco A. Casanova, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 793 - 818 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] algorithme de recherche [Termes IGN] appariement sémantique [Termes IGN] exploration de données [Termes IGN] image Flickr [Termes IGN] information sémantique [Termes IGN] intelligence artificielle [Termes IGN] langage de requête [Termes IGN] RDF [Termes IGN] SPARQL Résumé : (auteur) Stop-and-move semantic trajectories are segmented trajectories where the stops and moves are semantically enriched with additional data. A query language for semantic trajectory datasets has to include selectors for stops or moves based on their enrichments and sequence expressions that define how to match the results of selectors with the sequence the semantic trajectory defines. This article addresses the problem of searching semantic trajectories, using stop-and-move sequence expressions. The article first proposes a formal framework to define semantic trajectories and introduces stop-and-move sequence expressions, with well-defined syntax and semantics, which act as an expressive query language for semantic trajectories. Then, it describes a concrete semantic trajectory model in RDF, defines SPARQL stop-and-move sequence expressions and discusses strategies to compile such expressions into SPARQL queries. Lastly, the article specifies user-friendly keyword search expressions over semantic trajectories based on the use of keywords to specify stop-and-move queries, and the adoption of terms with predefined semantics to compose sequence expressions. It then shows how to compile such keyword search expressions into SPARQL queries. Finally, it provides a proof-of-concept experiment over a semantic trajectory dataset constructed with user-generated content from Flickr, combined with Wikipedia data. Numéro de notice : A2021-270 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1793157 date de publication en ligne : 20/07/2020 En ligne : https://doi.org/10.1080/13658816.2020.1793157 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97328 [article]

Semantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 6 (December 2020) . - 1482 - 1503 Titre : Semantic‐based urban growth prediction Type de document : Article/Communication Auteurs : Marvin Mc Cutchan, Auteur ; Simge Özdal‐Oktay, Auteur ; Ioannis Giannopoulos, Auteur Année de publication : 2020 Article en page(s) : 1482 - 1503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] croissance urbaine [Termes IGN] dynamique spatiale [Termes IGN] Europe (géographie politique) [Termes IGN] information sémantique [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] occupation du sol [Termes IGN] OpenStreetMap [Termes IGN] organisation spatiale [Termes IGN] OWL [Termes IGN] prévision [Termes IGN] réseau neuronal artificiel [Termes IGN] urbanisation [Termes IGN] ville durable Résumé : (Auteur) Urban growth is a spatial process which has a significant impact on the earth’s environment. Research on predicting this complex process makes it therefore especially fruitful for decision‐making on a global scale, as it enables the introduction of more sustainable urban development. This article presents a novel method of urban growth prediction. The method utilizes geospatial semantics in order to predict urban growth for a set of random areas in Europe. For this purpose, a feature space representing geospatial configurations was introduced which embeds semantic information. Data in this feature space was then used to perform deep learning, which ultimately enables the prediction of urban growth with high accuracy. The final results reveal that geospatial semantics hold great potential for spatial prediction tasks. Numéro de notice : A2020-766 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12655 date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1111/tgis.12655 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96657 [article]

Semantic trajectory segmentation based on change-point detection and ontology / Yuan Gao in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 12 (December 2020) . - pp 2361 - 2394 Titre : Semantic trajectory segmentation based on change-point detection and ontology Type de document : Article/Communication Auteurs : Yuan Gao, Auteur ; Longfei Huang, Auteur ; Jun Feng, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2361 - 2394 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cible mobile [Termes IGN] détection de changement [Termes IGN] information sémantique [Termes IGN] modèle dynamique [Termes IGN] objet mobile [Termes IGN] ontologie [Termes IGN] point d'intérêt [Termes IGN] probabilité [Termes IGN] segmentation sémantique [Termes IGN] trajectoire Résumé : (auteur) Trajectory segmentation is a fundamental issue in GPS trajectory analytics. The task of dividing a raw trajectory into reasonable sub-trajectories and annotating them based on moving subject’s intentions and application domains remains a challenge. This is due to the highly dynamic nature of individuals’ patterns of movement and the complex relationships between such patterns and surrounding points of interest. In this paper, we present a framework called SEMANTIC-SEG for automatic semantic segmentation of trajectories from GPS readings. For the decomposition component of SEMANTIC-SEG, a moving pattern change detection (MPCD) algorithm is proposed to divide the raw trajectory into segments that are homogeneous in their movement conditions. A generic ontology and a spatiotemporal probability model for segmentation are then introduced to implement a bottom-up ontology-based reasoning for semantic enrichment. The experimental results on three real-world datasets show that MPCD can more effectively identify the semantically significant change-points in a pattern of movement than four existing baseline methods. Moreover, experiments are conducted to demonstrate how the proposed SEMANTIC-SEG framework can be applied. Numéro de notice : A2020-689 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1798966 date de publication en ligne : 04/08/2020 En ligne : https://doi.org/10.1080/13658816.2020.1798966 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96226 [article]

The position of sound in audiovisual maps: an experimental study of performance in spatial memory / Nils Siepmann in Cartographica, vol 55 n° 2 (Summer 2020)  

Public [article]  inCartographica > vol 55 n° 2 (Summer 2020) . - pp 136 - 150 Titre : The position of sound in audiovisual maps: an experimental study of performance in spatial memory Type de document : Article/Communication Auteurs : Nils Siepmann, Auteur ; Dennis Edler, Auteur ; Julian Keil, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 136 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique [Termes IGN] audiovisuel [Termes IGN] carte cognitive [Termes IGN] communication cartographique [Termes IGN] document sonore [Termes IGN] information géographique [Termes IGN] information sémantique [Termes IGN] mémoire [Termes IGN] multimedia Résumé : (auteur) Digital maps are known as reliable media for communicating spatial information. People use maps to make themselves familiar with new environments and to form cognitive representations of spatial configurations and additional semantic information that are coupled with locational information. Since the mid-1990s, cartographers have explored auditory media as cartographic elements to transfer spatial information. Among the established sound variants used in multimedia cartography, speech recordings are a popular auditory tool to enrich the visual dominance of maps. The impact of auditory elements on human spatial memory has hardly been investigated so far in cartography and spatial cognition. A recent study showed that spoken object names bound to visual location markers affect performance in memory of object locations. Map users tend to make significantly smaller spatial distortion errors in the recall of object locations if these locations are coupled with auditory semantic information (place names). The present study extends this approach by examining possible effects on sound position as cues for spatial memory performance. A monaural condition, where an auditory name is presented in a spatial location corresponding to the object location, is compared with a binaural condition (of no directional cue). The results show that a monaural communication additionally improves spatial memory performance. Interestingly, the semantic information bound to an object location appears to be the driving factor in improving this effect. Numéro de notice : A2020-441 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2019-0008 date de publication en ligne : 16/06/2020 En ligne : https://doi.org/10.3138/cart-2019-0008 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95499 [article]

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