Source code and data are available online: https://gitlab.com/Tachella/real-time-single-photon-lidar
Tachella, J., Altmann, Y., Mellado, N. et al. Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers.
Nat Commun 10, 4984 (2019) doi:10.1038/s41467-019-12943-7
OpenGR is a set C++ libraries for 3D Global Registration. It is a fork of the Super4PCS library, and aims at providing several state of the art global registration algorithms for 3d data.
This fork is maintained by the same authors as the Super4PCS library. …
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A multi-purpose modular 3d engine developed in our computer graphics group.
The Super4PCS library is now part of the OpenGR library.
The Super4PCS is still available on github, but its development is discontinued. Switching to OpenGR will allow you to use Super4PCS alongside other registration algorithms, with a better API and more.
This software won the SGP Software Award 2017.
Data acquisition in large-scale scenes regularly involves accumulating information across multiple scans. A common approach is to locally align scan pairs using Iterative Closest Point (ICP) algorithm (or its variants), but requires static scenes and small motion between scan pairs. This prevents accumulating data across multiple scan sessions and/or different acquisition modalities (e.g., stereo, depth scans). Alternatively, one can use a global registration algorithm allowing scans to be in arbitrary initial poses. The state-of-the-art global registration algorithm, 4PCS, however has a quadratic time complexity in the number of data points. This vastly limits its applicability to acquisition of large environments. We present Super 4PCS for global pointcloud registration that is optimal, i.e., runs in linear time (in the number of data points) and is also output sensitive in the complexity of the alignment problem based on the (unknown) overlap across scan pairs. Technically, we map the algorithm as an instance problem and solve it efficiently using a smart indexing data organization. The algorithm is simple, memory-efficient, and fast. We demonstrate that Super 4PCS results in significant speedup over alternative approaches and allows unstructured efficient acquisition of scenes at scales previously not possible. Complete source code and datasets are available for research use at http://geometry.cs.ucl.ac.uk/projects/2014/super4PCS/.
Patate is a header only C++/CUDA library for graphics applications released under the MPL license.
It provides a collection of Computer Graphics techniques that incorporate the latest innovations from 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, organized in modules that each tackle a specific set of issues. 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. Modules will be dealing with graphics domains as varied as multi-scale analysis, material appearance, vector graphics, expressive rendering and 2D animation. Okay, right now only multi-scale analysis and vector graphics modules are available, but if everything goes as planned, this sentence should be properly deleted soon !
Patate is developed in collaboration with