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Constant Size Point Cloud Clustering: a Compact, Non-Overlapping Solution

2020Journal article Restricted access
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dc.contributor.authorGuarda, André F. R.
dc.contributor.authorRodrigues, Nuno M. M.
dc.contributor.authorPereira, Fernando
dc.date.accessioned2020-12-16T11:06:23Z
dc.date.available2020-12-16T11:06:23Z
dc.date.issued2020
dc.date.updated2020-12-04T16:30:45Z
dc.description.abstractPoint clouds have recently become a popular 3D representation model for many application domains, notably virtual and augmented reality. Since point cloud data is often very large, processing a point cloud may require that it be segmented into smaller clusters. For example, the input to deep learning-based methods like auto-encoders should be constant size point cloud clusters, which are ideally compact and non-overlapping. However, given the unorganized nature of point clouds, defining the specific data segments to code is not always trivial. This paper proposes a point cloud clustering algorithm which targets five main goals: i) clusters with a constant number of points; ii) compact clusters, i.e. with low dispersion; iii) non-overlapping clusters, i.e. not intersecting each other; iv) ability to scale with the number of points; and v) low complexity. After appropriate initialization, the proposed algorithm transfers points between neighboring clusters as a propagation wave, filling or emptying clusters until they achieve the same size. The proposed algorithm is unique since there is no other point cloud clustering method available in the literature offering the same clustering features for large point clouds at such low complexitypt_PT
dc.description.versioninfo:eu-repo/semantics/acceptedVersionpt_PT
dc.identifier.doi10.1109/tmm.2020.2974325pt_PT
dc.identifier.issn1520-9210
dc.identifier.issn1941-0077
dc.identifier.slugcv-prod-2105693
dc.identifier.urihttp://hdl.handle.net/10400.8/5229
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.subjectPoint cloudpt_PT
dc.subjectPoint cloud clusteringpt_PT
dc.subjectConstant sizept_PT
dc.subjectCompactnesspt_PT
dc.subjectNon-overlappingpt_PT
dc.titleConstant Size Point Cloud Clustering: a Compact, Non-Overlapping Solutionpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleIEEE Transactions on Multimediapt_PT
person.familyNameGuarda
person.familyNameM. M. Rodrigues
person.familyNameBernardo Pereira
person.givenNameAndré
person.givenNameNuno
person.givenNameFernando Manuel
person.identifier.ciencia-idF811-146F-4EE9
person.identifier.ciencia-id8010-A48A-90F0
person.identifier.orcid0000-0001-5996-1074
person.identifier.orcid0000-0001-9536-1017
person.identifier.orcid0000-0001-6100-947X
person.identifier.scopus-author-id7006052345
person.identifier.scopus-author-id55952373800
rcaap.cv.cienciaid6917-B121-4E34 | Nuno Miguel Morais Rodrigues
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationab4d7e6e-b391-49ba-a618-a52fc62c8837
relation.isAuthorOfPublicationb4ebe652-7f0e-4e67-adb0-d5ea29fc9e69
relation.isAuthorOfPublicationcb14fa15-4cd7-4d35-ba91-c4ad2d634549
relation.isAuthorOfPublication.latestForDiscoveryb4ebe652-7f0e-4e67-adb0-d5ea29fc9e69

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