Reference : SMART POINT CLOUD: DEFINITION AND REMAINING CHALLENGES
Scientific congresses and symposiums : Paper published in a journal
Engineering, computing & technology : Computer science
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
Engineering, computing & technology : Architecture
http://hdl.handle.net/2268/202970
SMART POINT CLOUD: DEFINITION AND REMAINING CHALLENGES
English
[en] Smart Point Cloud: Definition and remaining challenges
[fr] Vers les nuages de points intelligents: definition et challenges
[de] Smart-Punktwolke : Definition, Herausforderungen
[nl] smart puntenwolk: definitie en de resterende uitdagingen
[es] inteligente de nubes de puntos: definición y retos pendientes
[it] nuvola di punti intelligente: definizione e le sfide rimanenti
Poux, Florent mailto [Université de Liège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Neuville, Romain mailto [Université de Liège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Hallot, Pierre mailto [Université de Liège > Département de géographie > Architecture Site Lambert Lombard >]
Billen, Roland mailto [Université de Liège > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
5-Oct-2016
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Copernicus Publications
IV-2
W1
11th 3D GeoInfo Conference
119-127
Yes (verified by ORBi)
No
International
2194-9042
2194-9050
Göttingen
Germany
11th 3D GEOINFO CONFERENCE
du 18 octobre au 21 octobre 2016
ISPRS (International Society of Photogrammetry and Remote Sensing
Efi Dimopoulou
Peter Van Oosterom
Athens
Greece
[en] Point cloud data structure ; classification ; feature extraction ; segmentation ; data mining ; machine learning ; multi-dimensional indexing ; point cloud database
[en] Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/2268/202970
10.5194/isprs-annals-IV-2-W1-1-2016
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W1/119/2016/
https://www.academia.edu/29467954/SMART_POINT_CLOUD_DEFINITION_AND_REMAINING_CHALLENGES

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