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DARE
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Density Adaptive Point Set Registration
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DARE
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# 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>
