Point Clouds as an Efficient Multiscale Layered Spatial Representation

dc.contributor.authorPoux, Florenten_US
dc.contributor.authorNeuville, Romainen_US
dc.contributor.authorHallot, Pierreen_US
dc.contributor.authorBillen, Rolanden_US
dc.contributor.editorVincent Tourre and Filip Biljeckien_US
dc.date.accessioned2016-12-07T17:24:00Z
dc.date.available2016-12-07T17:24:00Z
dc.date.issued2016
dc.description.abstract3D point clouds describe urban shape at different scales, precisions and resolutions depending on the underlying sensors and acquisition methodology. These factors influence the quality of the data, as well as its representativity. In this paper, we propose a multi-scale workflow to obtain a better description of the captured environment through a multi-scale representative point cloud, presenting an unlimited depth and multisensory data fusion. Our method is shown over a ''smart point cloud'' data structure and based on data fusion principles retaining higher description and precision on overlapping areas. The concept is illustrated through a use case on the castle of Jehay (Belgium), where aerial LiDAR data, terrestrial laser scanner point cloud and photogrammetrybased reconstruction are combined to obtain a multi-scale data structure.en_US
dc.description.sectionheadersModelling
dc.description.seriesinformationEurographics Workshop on Urban Data Modelling and Visualisation
dc.identifier.doi10.2312/udmv.20161417
dc.identifier.isbn978-3-03868-013-0
dc.identifier.issn2307-8251
dc.identifier.pages31-36
dc.identifier.urihttps://doi.org/10.2312/udmv.20161417
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/udmv20161417
dc.publisherThe Eurographics Associationen_US
dc.subjectI.2.10 [Artificial Intelligence]
dc.subjectVision and Scene Understanding
dc.subjectIntensity
dc.subjectcolor
dc.subjectphotometry
dc.subjectthresholding
dc.subjectRepresentations
dc.subjectdata structures
dc.subjecttransforms
dc.titlePoint Clouds as an Efficient Multiscale Layered Spatial Representationen_US
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