Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/153439
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dc.contributor.authorLv, Chenleien_US
dc.contributor.authorLin, Weisien_US
dc.contributor.authorZhao, Baoquanen_US
dc.date.accessioned2021-12-02T06:07:03Z-
dc.date.available2021-12-02T06:07:03Z-
dc.date.issued2021-
dc.identifier.citationLv, C., Lin, W. & Zhao, B. (2021). Approximate intrinsic voxel structure for point cloud simplification. IEEE Transactions On Image Processing, 30, 7241-7255. https://dx.doi.org/10.1109/TIP.2021.3104174en_US
dc.identifier.issn1057-7149en_US
dc.identifier.urihttps://hdl.handle.net/10356/153439-
dc.description.abstractA point cloud as an information-intensive 3D representation usually requires a large amount of transmission, storage and computing resources, which seriously hinder its usage in many emerging fields. In this paper, we propose a novel point cloud simplification method, Approximate Intrinsic Voxel Structure (AIVS), to meet the diverse demands in real-world application scenarios. The method includes point cloud preprocessing (denoising and down-sampling), AIVS-based realization for isotropic simplification and flexible simplification with intrinsic control of point distance. To demonstrate the effectiveness of the proposed AIVS-based method, we conducted extensive experiments by comparing it with several relevant point cloud simplification methods on three public datasets, including Stanford, SHREC, and RGB-D scene models. The experimental results indicate that AIVS has great advantages over peers in terms of moving least squares (MLS) surface approximation quality, curvature-sensitive sampling, sharp-feature keeping and processing speed.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.language.isoenen_US
dc.relationMOE2016-T2-2-057(S)en_US
dc.relation.ispartofIEEE Transactions on Image Processingen_US
dc.rights© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TIP.2021.3104174.en_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Computer graphicsen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Image processing and computer visionen_US
dc.titleApproximate intrinsic voxel structure for point cloud simplificationen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.contributor.researchMultimedia & Interactive Computing Laben_US
dc.identifier.doi10.1109/TIP.2021.3104174-
dc.description.versionAccepted versionen_US
dc.identifier.volume30en_US
dc.identifier.spage7241en_US
dc.identifier.epage7255en_US
dc.subject.keywordsPoint Cloud Simplificationen_US
dc.subject.keywordsIsotropic Simplificationen_US
dc.description.acknowledgementThis work was supported by the Ministry of Education, Singapore through the Tier- 2 Fund under Grant MOE2016-T2-2-057(S).en_US
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