The CloudCompare project by Dr. Daniel Girardeau-Montaut

Transcript

1. This slide was made by Dr. Daniel Girardeau-Montaut and presented

   in CloudCompare Meetup 2024 in University of Tokyo, Japan.

2. The CloudCompare project www.cloudcompare.org @CloudCompareGPL [email protected] 17 April 2024, Tokyo,

   Japan

3. 2003: PhD for EDF R&D  EDF ⚫ Main French

   power utility ⚫ ~170 000 employees worldwide 2 000 @ EDF R&D ⚫ > 400 dams + 56 nuclear reactors (18 plants)

4. EDF and Laser Scanning EDF = former owner of Mensi

   (now Trimble Laser Scanning) Main scanning activity: as-built documentation Scanning a single nuclear reactor building: ⚫ 2002: 3 days, 50 M. points ⚫ 2014: 1.5 days, 50 Bn points (+ high res. photos)

5. EDF and Laser Scanning  Other scanning activities: ⚫ Building

   monitoring (dams, cooling towers, etc.) ⚫ Landslide monitoring ⚫ Hydrology ⚫ Historical preservation (EDF Foundation)

6. PhD  Change detection on 3D geometric data ⚫ Application

   to Emergency Mapping  Inspired by 9/11 post-attacks recovery efforts (see “Mapping Ground Zero” by J. Kern, Optech, Nov. 2001) TLS was used for: visualization, optimal crane placement, measurements, monitoring the subsidence of the wreckage pile, slurry wall monitoring, etc.

7. CloudCompare V1  2004-2006  Aim: quickly detecting changes by

   comparing TLS point clouds… ⚫ with a CAD model ⚫ or with another high density cloud

8. CloudCompare V2  2006-2007: “Industrialization” of CloudCompare ⚫ for internal

   use only! ⚫ EDF is not a software company  Idea: make it Open Source ⚫ can still work on it even if not an EDF employee anymore ⚫ maintained and improved by the community

9. The open-source path  2009/2010: CloudCompare V2.1 ⚫ Already a

   multi-purpose point cloud editing and processing software  2017: CloudCompare V2.8  2019: CloudCompare V2.11  2024: CloudCompare V2.13 Runs on: Windows Linux macOS (sometimes) Support for 3D mouse & stereo displays

10. Open Source!  Evolves quickly…  … in the direction

    users want (faster if users actively participate to the developments ☺)  Remains under close supervision of its administrator  Manufacturer independent  Supported by various companies and public institutions (EDF, BRGM, CNRS, etc.)

11. Open Source!  Free…  …however, someone still needs to

    pay ;) ⚫ either by developing new functionalities ⚫ or by paying someone else to do it  Plugins are not necessarily open-source or free

12. Users Developers  Too many ⚫ Academics: • remote sensing

    • geology • archeology • etc. ⚫ Surveyors ⚫ Forensic experts ⚫ Architects ⚫ MDs, dentists ⚫ 3D designers ⚫ Artist?!  Barely enough ⚫ a few PhD students or research engineers ⚫ none ⚫ 1 ⚫ none ⚫ none ⚫ none ⚫ none

13. SW development cycle Specs algorithm “packaging” (GUI, details, etc.) tests

    simple forum message the best part less funny developer’s hell user’s hell stability time First release users feedback!

14. Worldwide > 108k downloads in 6 months (Windows version) >

    5500 users registered to the newsletter

15. User meetups and conferences  2014: IAFSM 1st Intl Conference

    (Orlando, USA)  2015: Cicese Point Cloud Workshop (Ensenada, Mexico)  2016: JIAP (Paris Sorbonne, France)  2016: Virtual Geosciences Conference (Bergen, Norway)  2017: ARCH3D (Nafplio, Greece)  2018: JBGE (Lausanne, Switzerland)  2019: Point Cloud Processing Workshop (Stuttgart, Germany)  2020: CloudCompare Dev Course (Paris-Saclay, France)  2021: Consortium 3D pour les SHS (Remote, France)  2021: Virtual Geosciences Conference (Marseilles, France)  2022: Point Clouds and change detection in the geosciences (Remote, France)  2023: Silvilaser (London, UK)  etc.  2024: Tokyo, Japan!

16. Citations in scientific articles source: Google scholar 0 200 400

    600 800 1000 1200 2012 2013 2014 2015 2016 2017 2018 2019

17. Latest release: 2.13.1  Release on the 14th of February

    2024 ⚫ huge list of improvements and new features ⚫ brand new LAS files support ⚫ new plugins: 3Dmasc, TreeIso, 3DFin 2.13.0: https://www.cloudcompare.org/release/notes/20240214/ 2.13.1: https://www.cloudcompare.org/release/notes/20240320/

18. Quick overview

19. Interface

20. Inputs / outputs  point clouds ⚫ ASCII, PLY, LAS,

    E57, PTX, PCD… + Faro, Riegl, DotProduct  triangular meshes ⚫ OBJ, PLY, STL, OFF, FBX  polylines ⚫ SHP, DXF, etc.  rasters ⚫ geotiff, etc. (thanks to GDAL)  calibrated pictures ⚫ Bundler OUT, Photoscan PSZ  sensors ⚫ TLS or projective cameras + dedicated format: BIN (for projects)

21. Display capabilities 0-20M points 20M-100M mid-range 100M-500M high-range L.O.D. mechanism

    > 500 M. points? ⚫ for now, use the command line mode ⚫ later: out-of-core support?

22. Scalar fields  One value per point  The value

    can be anything (distance, intensity, density, roughness, confidence, curvature, temperature, time, etc.)  Values can be (dynamically) color-coded

23. Scalar fields  Values can be ⚫ mixed (+,-,/,x) ⚫

    transformed (cos, log, etc.) ⚫ filtered (spatial smoothing, spatial gradient, etc.) ⚫ imported or exported as a coordinate dimension ⚫ merged with colors ⚫ transferred to another entity (+ interpolated)  Statistics can be computed  Clouds can be processed based on those values ⚫ Segmentation (“Filter by value”) ⚫ Subsampling

24. Main features  Interactive tools ⚫ transformation, segmentation, cross section

     Colors ⚫ create, convert, level, etc.  Normals ⚫ create, convert, orient

25. Main features  Mesh operations ⚫ create (2.5D Delaunay), sample

    points, smooth, etc. ⚫ → see Meshlab for more  Scalar fields operations ⚫ filter points by value, convert, smooth, gradient, etc.  Point picking, Distance / angle measurements  Others ⚫ Subsample, merge, scale, etc.

26. Main tools  Registration ⚫ point-pair-based alignment, ICP  Distances

    ⚫ Cloud-to-cloud (C2C), Cloud-to-mesh (C2M), Cloud-to- primitive (C2P), Robust cloud-to-cloud (M3C2)

27. Main tools  Cleaning ⚫ SOR, etc.  Rasterize ⚫

    + contour plot  2.5D volume estimation

28. Main tools  Segmentation ⚫ connected components, profile extraction, etc.

     Fitting ⚫ plane, sphere, quadric, etc.

29. Main tools  Roughness, curvature, density and other geometric features

    computation Features: "Contour detection in unstructured 3D point clouds", Hackel et al, 2016

30. Advanced point cloud processing + Plugins

31. Built-in support  Octree structure (fast construction, fast kNN) 

    Sensors (TLS or Camera)  Scan grids (structured point clouds)  Full waveform  Plugins  Command line mode

32. M3C2  Robust + signed C2C distances ⚫ Search correspondances

    along surface normal ⚫ Multi-scale approach ⚫ Uncertainty estimation based on local surface roughness

33. Canupo  Point cloud classification ⚫ Multi-scale local dimensionality feature

    ⚫ SVM based training "3D Terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology", N. Brodu, D. Lague, 2012

34. 3DMASC  Advanced point cloud classification ⚫ https://lidar.univ-rennes.fr/en/3dmasc ⚫ Multiple

    Attributes, Scales and Clouds ⚫ Designed to classify bi-temporal or bi-spectral surveys ⚫ Fully configurable (mix any number of scalar fields, geometric features, colors, etc.) 3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-Spectral Topo-Bathymetric lidar data, M. Letard et al, 2023

35. Cloth Simulation Filter (CSF)  Ground points extraction from LiDAR

    point clouds "An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation", W. Zhang et al., 2016

36. Cloud Layers  Manual (re)labelling of point clouds  Works

    with any scalar field  (developed in Ukraine )

37. Other plugins  Automatic shape detection (Ransac Shape Detection) 

    Structural geology toolbox for the interpretation and analysis of virtual outcrop models (Compass)  Geological facet extraction (Facets)  Global illumination of clouds and meshes (PCV)  3D surface reconstruction (PoissonRecon)  Animation rendering (Animation)  Surface of Revolution Analysis (SRA)  Planar surfaces cleaning (Virtual Broom)  Hidden Points Removal (HPR)  etc.

38. Creating your own plugin…  … is easy: ⚫ copy

    the ‘dummy’ plugin folder ⚫ replace the word ‘dummy’ in all files by your plugin name ⚫ and add the code for your plugin ‘action’ at the right place  Plenty of examples ⚫ simply mimic another plugin that has the same workflow  Ask questions on the forum (or send me an email)  Development in C++ with Qt

39. Next steps  Ideas ⚫ from OpenGL to Vulkan? ⚫

    out-of-core support?  And always the ever-growing TODO list…

40. Thanks for your attention! www.cloudcompare.org

41. Some success stories

42. Classification of China's terracotta warriors ears Photogrammetry Segmentation Pair-wise comparison

    Classification (1) Computer vision, archaeological classification and China's terracotta warriors, A. Bevan et al. 2014

43. Analysis of construction work for a court case

44. Chambord Castle  Full documentation of the castle with: ⚫

    TLS scans ⚫ Photogrammetry (ground-based + UAV) ⚫ Panoramic images ⚫ Traditional survey points acquisition for georeferencing broadcasted on French TV ;)

45. Chambord Castle  Great communication tool  Useful for monitoring

    and maintenance work planning  Better understanding of the architecture (symmetries, role of some features and rooms, issues during the construction, etc.) → the whole dataset was delivered to the Castle’s curators with… CloudCompare!

46. The Dancers column of Delphi  Virtual reconstruction of the

    column ⚫ More than 260 marble fragments ⚫ More than 14 m. high A Point-Based Approach for Capture, Display and Illustration of Very Complex Archeological Artefacts Florent Duguet, George Drettakis, Daniel Girardeau-Montaut, Jean-Luc Martinez, Francis Schmitt, VAST (2004)

47. The Dancers column of Delphi ⚫ acquisition: > 1 week,

    2200 scans, 600 M. points (in 2004) ⚫ cleaning + segmentation (removal of plaster parts) → 220 M. points remaining ⚫ 600h of intensive 2D/3D virtual “puzzling” ⚫ lots of discussion + specific tools development (3 labs)

48. The Dancers column of Delphi  CloudCompare part: ⚫ unrolling

    ⚫ mesh quality assessment ⚫ global illumination of clouds (Shadevis / “PCV”) ⚫ visualization mesh (normals) mesh (PCV) photograph

49. The Dancers column of Delphi  Unrolling (Omphalos)

50. The Dancers column of Delphi Capital Drum 2

51. The Dancers column of Delphi

52. Comparison of scans in a cave  Cramped environment, few

    options for positioning the scanner → lots of occlusions

53. Comparison of scans in a cave → lots of false

    detections