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A Multilevel Road Alignment Model for Spatial-Query-by-Sketch
dc.contributor.author | Tang, Ming | |
dc.contributor.author | Falomir, Zoe | |
dc.contributor.author | Sheng, Yehua | |
dc.date.accessioned | 2021-01-11T11:22:28Z | |
dc.date.available | 2021-01-11T11:22:28Z | |
dc.date.issued | 2020-11-01 | |
dc.identifier.citation | TANG, Ming; FALOMIR, Zoe; SHENG, Yehua. A Multilevel Road Alignment Model for Spatial-Query-By-Sketch. Applied Sciences, 2020, vol. 10, no 21, p. 7685 | ca_CA |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | http://hdl.handle.net/10234/191143 | |
dc.description.abstract | A sketch map represents an individual’s perception of a specific location. However, the information in sketch maps is often distorted and incomplete. Nevertheless, the main roads of a given location often exhibit considerable similarities between the sketch maps and metric maps. In this work, a shape-based approach was outlined to align roads in the sketch maps and metric maps. Specifically, the shapes of main roads were compared and analyzed quantitatively and qualitatively in three levels pertaining to an individual road, composite road, and road scene. An experiment was performed in which for eight out of nine maps sketched by our participants, accurate road maps could be obtained automatically taking as input the sketch and the metric map. The experimental results indicate that accurate matches can be obtained when the proposed road alignment approach Shape-based Spatial-Query-by-Sketch (SSQbS) is applied to incomplete or distorted roads present in sketch maps and even to roads with an inconsistent spatial relationship with the roads in the metric maps. Moreover, highly similar matches can be obtained for sketches involving fewer roads. | ca_CA |
dc.format.extent | 26 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | MDPI | ca_CA |
dc.relation.isPartOf | Applied Sciences, 2020, vol. 10, no 21 | ca_CA |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | * |
dc.subject | cognitive map | ca_CA |
dc.subject | sketch map | ca_CA |
dc.subject | shape matching | ca_CA |
dc.subject | Spatial-Query-by-Sketch | ca_CA |
dc.subject | composite road matching | ca_CA |
dc.subject | scene matching for road networks | ca_CA |
dc.title | A Multilevel Road Alignment Model for Spatial-Query-by-Sketch | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.3390/app10217685 | |
dc.relation.projectID | National Natural Science Foundation of China (NSFC): 41631175; National Key Research and Development Program of China: 2017YFB0503500 | ca_CA |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://www.mdpi.com/2076-3417/10/21/7685/htm | ca_CA |
dc.contributor.funder | Part of this work was carried out while M.T. was a doctoral research fellow at the Bremen Spatial Cognition Center. Z.F. acknowledges funding by the Cognitive Qualitative Descriptions and Applications (CogQDA) project at the University of Bremen and also the Ramon y Cajal fellowship (RYC2019-027177-I/AEI/10.13039/501100011033) awarded by the Spanish Ministry of Science, Innovation and Universities. | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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