Work

Dynamic Point Cloud Compression Based on Projections, Surface Reconstruction and Video Compression

Year: 2021

Type: article

Abstract: 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-point and point-to-plane measures. Comprehensive experiments show better performance for some projection maps: cylindrical, Miller and Mercator projections.

Source: Sensors

DOI: 10.3390/s22010197

Authors: Emil Dumic, Anamaria Bjelopera, Andreas Nüchter

Institutions: University North, University of Dubrovnik, University of Würzburg

Language: English

Topic: Video Coding and Compression Technologies

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,376

Funder: Julius-Maximilians-Universität Würzburg