DARE

This repository contains a python implementation of the Density Adaptive Point Set Registration (DARE) method. Without the density adaptation, the method is equivalent to Joint Registration of Multiple Point Sets (JRMPC) [1]. Additionally, implementations of Color-based Probabilistic Point Set Registration (CPPSR) [2] and Feature-based Probabilistic Point Set Registration (FPPSR) [3] are provided and can be run together with the density adaptation.

The script reg_demo.py runs DARE on a subsampled version of the vps outdoor dataset.

This method is also included in https://github.com/felja633/RLLReg as a pytorch implementation.

Publication

A detailed description of the DARE method can be found in the CVPR 2018 paper:

F. Järemo Lawin, M. Danelljan, F. S. Khan, P.-E. Forssen, and M. Felsberg, “Density adaptive point set registration,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. https://arxiv.org/pdf/1804.01495.pdf

@InProceedings{jaremo18a,
  author = 	 {Felix J\"aremo Lawin and Martin Danelljan and Fahad Khan and Per-Erik Forss\'en and Michael Felsberg},
  title = 	 {Density Adaptive Point Set Registration},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition},
  year = 	 {2018},
  month = 	 {June},
  address = 	 {Salt Lake City, Utah, USA},
  publisher =    {Computer Vision Foundation},
}

Dependencies

python 3.6
numpy
scipy
matplotlib
pathlib
cmake
pcl (if you want to use FPPSR)

Installation

Make sure that the above dependencies are installed.

To be able to run FPPSR, you need to build the pybind module in src/pcl_utils at src/pcl_utils/build.

You may use the shell script build_pybind_modules. The code has been tested in Ubuntu 16.04 and 18.04.

Datasets

The full datasets used in the paper can be found at http://www.hdrv.org/vps/ and http://www.prs.igp.ethz.ch/research/completed_projects/automatic_registration_of_point_clouds.html.

Contact

Felix Järemo Lawin

email: felix.lawin@gmail.com

References

JRMPC: [1] G. D. Evangelidis, D. Kounades-Bastian, R. Horaud, and E. Z. Psarakis, “A generative model for the joint registration of multiple point sets,” in European Conference on Computer Vision, pp. 109–122, Springer, 2014 https://team.inria.fr/perception/research/jrmpc/

CPPSR: [2] M. Danelljan, G. Meneghetti, F. Shahbaz Khan, and M. Felsberg, “A prob- abilistic framework for color-based point set registration,” in CVPR, 2016. http://www.cvl.isy.liu.se/research/cogvis/colored-point-set-registration/index.html

FPPSR: [3] M. Danelljan, G. Meneghetti, F. Shahbaz Khan, and M. Felsberg, “Aligning the dissimilar: A probabilistic method for feature-based point set registration,” in ICPR, 2016. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7899641

felja633 / DARE