This paper presents novel compression method for dynamic
point clouds based on projections and the H.265/HEVC
video coder. We used 3DTK - The 3D Toolkit to create
equirect-angular projection images and x265 as
H.265/HEVC coder, to compress and extract created
projection images. Compression was introduced in
3DTK generated projection image size (differ-ent
pixel size, but compatible with later video
compression), as well as lossless/lossy video
compression. Visual inspection shows better results
for compression only using different projection
resolution, with lossless video compression. Lossy
video compression adds noise and creates additional
points, resulting in lower visual quality.
%0 Conference Paper
%1 SMGM_2019
%A Dumic, E.
%A Bjelopera, A.
%A Nüchter, A.
%B Proceedings of the 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET''19)
%C Split, Croatia
%D 2019
%I IEEE Xplore
%K imported myown
%P 1--4
%R https://doi.org/10.23919/SMAGRIMET.2019.8720392
%T Projection based dynamic point cloud compression using 3DTK
toolkit and H.265/HEVC
%U https://robotik.informatik.uni-wuerzburg.de/telematics/download/smagrimet2019.pdf
%X This paper presents novel compression method for dynamic
point clouds based on projections and the H.265/HEVC
video coder. We used 3DTK - The 3D Toolkit to create
equirect-angular projection images and x265 as
H.265/HEVC coder, to compress and extract created
projection images. Compression was introduced in
3DTK generated projection image size (differ-ent
pixel size, but compatible with later video
compression), as well as lossless/lossy video
compression. Visual inspection shows better results
for compression only using different projection
resolution, with lossless video compression. Lossy
video compression adds noise and creates additional
points, resulting in lower visual quality.
@inproceedings{SMGM_2019,
abstract = {This paper presents novel compression method for dynamic
point clouds based on projections and the H.265/HEVC
video coder. We used 3DTK - The 3D Toolkit to create
equirect-angular projection images and x265 as
H.265/HEVC coder, to compress and extract created
projection images. Compression was introduced in
3DTK generated projection image size (differ-ent
pixel size, but compatible with later video
compression), as well as lossless/lossy video
compression. Visual inspection shows better results
for compression only using different projection
resolution, with lossless video compression. Lossy
video compression adds noise and creates additional
points, resulting in lower visual quality.},
added-at = {2019-05-28T13:35:59.000+0200},
address = {Split, Croatia},
author = {{Dumic}, E. and {Bjelopera}, A. and {N{\"u}chter}, A.},
biburl = {https://www.bibsonomy.org/bibtex/2366aa627269c0320a947fa262bd2d84d/nuechter76},
booktitle = {Proceedings of the 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET''19)},
doi = {https://doi.org/10.23919/SMAGRIMET.2019.8720392},
interhash = {b36895563d492d74f25148c0b2aa48ea},
intrahash = {366aa627269c0320a947fa262bd2d84d},
keywords = {imported myown},
month = {April},
pages = {1--4},
publisher = {IEEE Xplore},
timestamp = {2019-05-28T13:39:53.000+0200},
title = {{Projection based dynamic point cloud compression using 3DTK
toolkit and H.265/HEVC}},
url = {https://robotik.informatik.uni-wuerzburg.de/telematics/download/smagrimet2019.pdf},
year = 2019
}