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Dynamic point cloud compression based on projections, surface reconstruction and video compression
Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-252231
- In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video compression is specific for geometry (FFV1) and texture (H.265/HEVC). Decompressed point clouds are reconstructed using a Poisson surface reconstruction algorithm. Comparison with the original point clouds was performed using point-to-pointIn this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video compression is specific for geometry (FFV1) and texture (H.265/HEVC). Decompressed point clouds are reconstructed using a Poisson surface reconstruction algorithm. Comparison with the original point clouds was performed using point-to-point and point-to-plane measures. Comprehensive experiments show better performance for some projection maps: cylindrical, Miller and Mercator projections.…
Autor(en): | Emil Dumic, Anamaria Bjelopera, Andreas Nüchter |
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URN: | urn:nbn:de:bvb:20-opus-252231 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Sensors |
ISSN: | 1424-8220 |
Erscheinungsjahr: | 2021 |
Band / Jahrgang: | 22 |
Heft / Ausgabe: | 1 |
Aufsatznummer: | 197 |
Originalveröffentlichung / Quelle: | Sensors (2022) 22:1, 197. https://doi.org/10.3390/s22010197 |
DOI: | https://doi.org/10.3390/s22010197 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Freie Schlagwort(e): | 3DTK toolkit; Poisson surface reconstruction; map projections; octree; point cloud compression; point-to-plane measure; point-to-point measure |
Datum der Freischaltung: | 18.11.2022 |
Datum der Erstveröffentlichung: | 28.12.2021 |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |