The Point Cloud Library (or PCL) is a large scale, open project [1] for 2D/3D image and point cloud processing. The PCL framework contains numerous state-of-the art algorithms including filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. These algorithms can be used, for example, to filter outliers from noisy data, stitch 3D point clouds together, segment relevant parts of a scene, extract keypoints and compute descriptors to recognize objects in the world based on their geometric appearance, and create surfaces from point clouds and visualize them -- to name a few.

References in zbMATH (referenced in 17 articles )

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  1. Choi, Gary P. T.; Liu, Yechen; Lui, Lok Ming: Free-boundary conformal parameterization of point clouds (2022)
  2. Ales Jelinek, Adam Ligocki, Ludek Zalud: Robotic Template Library (2021) arXiv
  3. Shukla, Khemraj; Jagtap, Ameya D.; Karniadakis, George Em: Parallel physics-informed neural networks via domain decomposition (2021)
  4. Kudela, László; Kollmannsberger, Stefan; Almac, Umut; Rank, Ernst: Direct structural analysis of domains defined by point clouds (2020)
  5. Skrodzki, Martin; Zimmermann, Eric; Polthier, Konrad: Variational shape approximation of point set surfaces (2020)
  6. Tibo, Alessandro; Jaeger, Manfred; Frasconi, Paolo: Learning and interpreting multi-multi-instance learning networks (2020)
  7. Zhang, Wenxiao; Long, Chengjiang; Yan, Qingan; Chow, Alix L. H.; Xiao, Chunxia: Multi-stage point completion network with critical set supervision (2020)
  8. Gao, Tingran; Kovalsky, Shahar Z.; Daubechies, Ingrid: Gaussian process landmarking on manifolds (2019)
  9. Sebastian Lamprecht: Pyoints: A Python package for point cloud, voxel and raster processing (2019) not zbMATH
  10. Sun, Da; Liao, Qianfang; Stoyanov, Todor; Kiselev, Andrey; Loutfi, Amy: Bilateral telerobotic system using type-2 fuzzy neural network based moving horizon estimation force observer for enhancement of environmental force compliance and human perception (2019)
  11. Zhong, Sikai; Zhong, Zichun; Hua, Jing: Surface reconstruction by parallel and unified particle-based resampling from point clouds (2019)
  12. Bülow, Heiko; Birk, Andreas: Scale-free registrations in 3D: 7 degrees of freedom with Fourier Mellin SOFT transforms (2018)
  13. Slavcheva, Miroslava; Kehl, Wadim; Navab, Nassir; Ilic, Slobodan: SDF-2-SDF registration for real-time 3D reconstruction from RGB-D data (2018)
  14. Sveier, Aksel; Kleppe, Adam Leon; Tingelstad, Lars; Egeland, Olav: Object detection in point clouds using conformal geometric algebra (2017)
  15. Ansari, Zafar Ahmed; Harit, Gaurav: Nearest neighbour classification of Indian sign language gestures using kinect camera (2016) ioport
  16. Wilkowski, Artur; Kornuta, Tomasz; Stefańczyk, Maciej; Kasprzak, Włodzimierz: Efficient generation of 3D surfel maps using RGB-D sensors (2016)
  17. Lehment, Nicolas; Kaiser, Moritz; Rigoll, Gerhard: Using segmented 3D point clouds for accurate likelihood approximation in human pose tracking (2013) ioport