Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Stefan Ohrhallinger"'
Publikováno v:
The Visual Computer
Large-scale unstructured point cloud scenes can be quickly visualized without prior reconstruction by utilizing levels-of-detail structures to load an appropriate subset from out-of-core storage for rendering the current view. However, as soon as we
Publikováno v:
Computer Graphics Forum. 39:155-167
Autor:
Tamal K. Dey, Stefan Ohrhallinger, Jiju Peethambaran, Amal Dev Parakkat, Ramanathan Muthuganapathy
Curve reconstruction from unstructured points in a plane is a fundamental problem with many applications that has generated research interest for decades. Involved aspects like handling open, sharp, multiple and non-manifold outlines, run-time and pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1917fcbcf07fa19c0c3d642040b33c3f
Publikováno v:
Graphics Interface 2014 ISBN: 9781003059325
Graphics Interface
Graphics Interface
A recent trend in interactive environments is the use of unstructured and temporally varying point clouds. This is driven by both affordable depth cameras and augmented reality simulations. One research question is how to perform collision detection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1403c02753fedad80415556573c3cab9
https://doi.org/10.1201/9781003059325-4
https://doi.org/10.1201/9781003059325-4
The design of functional seating furniture is a complicated process which often requires extensive manual design effort and empirical evaluation. We propose a computational design framework for pose-driven automated generation of body-supports which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46513e305629f66008d905f4cbbadb39
http://arxiv.org/abs/2003.10435
http://arxiv.org/abs/2003.10435
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585570
ECCV (5)
ECCV (5)
A key step in any scanning-based asset creation workflow is to convert unordered point clouds to a surface. Classical methods (e.g., Poisson reconstruction) start to degrade in the presence of noisy and partial scans. Hence, deep learning based metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1976cc1282c51e08d9520edcd8d051a3
https://doi.org/10.1007/978-3-030-58558-7_7
https://doi.org/10.1007/978-3-030-58558-7_7
Autor:
Michael Wimmer, Stefan Ohrhallinger
Publikováno v:
Computer Graphics Forum. 38:126-137
Publikováno v:
Computer Graphics Forum. 35:167-176
We consider the problem of sampling points from a collection of smooth curves in the plane, such that the Crust family of proximity-based reconstruction algorithms can rebuild the curves. Reconstruction requires a dense sampling of local features, i.
Publikováno v:
Computers & Graphics. 37:645-658
Most methods for interpolating unstructured point clouds handle densely sampled point sets quite well but get into trouble when the point set contains regions with much sparser sampling, a situation often encountered in practice. In this paper, we pr
Autor:
Sudhir P. Mudur, Stefan Ohrhallinger
Publikováno v:
Computer Graphics Forum. 32:72-88
We present an efficient algorithm for determining an aesthetically pleasing shape boundary connecting all the points in a given unorganised set of 2D points, with no other information than point coordinates. By posing shape construction as a minimisa