Model-Centric Volumetric Point Cloud Attributes
Ricardo L. de Queiroz, Camilo Dorea, Davi R. Freitas, Maja Krivokuca,, Gustavo P. Sandri

TL;DR
This paper introduces a model-centric volumetric approach to describe point cloud attributes, enabling independent rendering of 3D objects with complex optical properties like transparency and translucency.
Contribution
It proposes a novel set of seven electromagnetic-based attributes per voxel to describe material and color properties independently of illumination and camera position.
Findings
Attributes enable rendering of transparent and translucent objects.
Model-centric description is independent of illumination and camera.
Supports complex phenomena like fog, smoke, and mirrors.
Abstract
Point clouds have recently gained interest, especially for real-time applications and for 3D-scanned material, such as is used in autonomous driving, architecture, and engineering, to model real estate for renovation or display. Point clouds are associated with geometry information and attributes such as color. Be the color unique or direction-dependent (in the case of plenoptic point clouds), it reflects the colors observed by cameras displaced around the object. Hence, not only are the viewing references assumed, but the illumination spectrum and illumination geometry is also implicit. We propose a model-centric description of the 3D object, that is independent of the illumination and of the position of the cameras. We want to be able to describe the objects themselves such that, at a later stage, the rendering of the model may decide where to place illumination, from which it may…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputer Graphics and Visualization Techniques · 3D Shape Modeling and Analysis · Advanced Numerical Analysis Techniques
