About Ponca

Ponca is a header only library coded in C++, and compatible with CUDA. It is maintained by researchers in Computer Graphics, and released under the MPL license. Source code is available at: https://github.com/poncateam/ponca

Ponca provides a collection of techniques for Point Cloud Analysis that incorporate the latest innovations from CNRS and INRIA research teams working in the field. It strives for efficiency and ease-of-use by focusing on low-level core operators and key algorithms. The central goal of the library is to drastically reduce the time and efforts required to turn a research paper into a ready-to-use solution, for both commercial and academic purposes.

The library is still in its infancy and we're actively working on it to bring you the latest of our published research techniques.

Basic FAQs

How do I get Ponca to work with my computer?
If by that you mean "How can I download and install your library?", then the best place to start is the Getting started section, as you might have guessed from the onset.
What can I develop with Ponca? Do you have code examples?
I guess you're looking for a User Manual, or even an Examples page? This might give you enough suggestions to start experimenting with your own recipies.
Where do these approaches come from originally?
The Ponca library relies on published scientific papers that we have collected in the Bibliography section of the documentation. These will prove useful if you want to dig into the implementation of operators and algorithms. If the Ponca library contributes to a project that leads to a scientific publication or a commercial or free software, all we ask is to tell us about it, or at least cite the project using the bibtex entry provided at the end of this page.
What can I do if I get mashed in trouble?
If you get stuck or have a problem/bug using Ponca, open an issue on Github for further assistance. Remember that the library is under development so we are pleased to get your feedback.
What does "Ponca" mean, actually?
"Ponca" stands for POiNt Cloud Analysis. Currently, it provides fitting techniques and spatial queries accelerators (e.g. KdTree), to approximate sets of points by planes or spheres. Upcoming release should bring Moving Least Squares surfaces.
How is Ponca licensed?
The source code of the library is licensed under the Mozilla Public License (MPL), v. 2.0. Its main advantage is to grant inclusion of template files as long as the source code itself is not modified. For more details, a copy of the MPL can be found at http://mozilla.org/MPL/2.0/ .

Credits

Developers and contributors

Main contributors

Nicolas Mellado : conception, implementation, documentation and examples
Thibault Lejemble : implementation of several fitting primitives, differential estimators, and original version of the Spatial Partitioning code

Other contributors

Fitting module : Aniket Agarwalla, Nicolas Dupont, Carl Delrieu, Dorian Verge, Jules Vidal, Antoine Lafon, Anais Bains
SpatialPartitioning module : Amael Marquez, Matthieu Gomiero, Dorian Ferreira, Sacha Vincent

Patate/Grenaille crew and contributors

Ponca is a fork of Patate, module Grenaille, which is now deprecated, and which was developed by:

Nicolas Mellado : conception, implementation and examples
Gael Guennebaud : conception and implementation
Pascal Barla : conception and documentation
Patrick Reuter : conception and documentation
Thibault Lejemble : implementation
Gautier Ciaudo : testing, documentation, refactoring and examples
Noam Kremen : implementation

Citation

If you use our library, please cite it using the following bibtex entry:

  @MISC{Ponca,
  author = {Nicolas Mellado and Thibault Lejemble and Ga\"{e}l Guennebaud and Pascal Barla and others},
  title = {Ponca: a Point Cloud Analysis Library},
  howpublished = {https://github.com/poncateam/ponca/},
  year = {2020}
  }

Users

Inria - Manao Team
IRIT - STORM Team