Clouds of points - where I can find?

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Clouds of points - where I can find?

tstanley
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Hi,

I'm new with PCL, its my first project and I still have some basic problems.
One of the most important is, that I can not find Point Clouds in the internet.

I'm trying to ipmlement ICP algorithm, and I need some input data (Point Clouds) to test it.
If you can give me some advice (or link maybe), where I can download it, I would be VERY greatfull!

Thanks for your help.
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Re: Clouds of points - where I can find?

MungoMan
I found some pcd-file here:
http://svn.pointclouds.org/data/tutorials/
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Re: Clouds of points - where I can find?

hielsber
In reply to this post by tstanley
PCL has a nice repository here that contains point clouds in a format you should be able to read easily.  For more data sets (in various formats) see the following links.  Most of the data below is free to use for educational work; for other purposes you should see licenses for detail.

  - Robotic 3D Scan Repository
  - Radish: The Robotics Data Set Repository
  - Canadian Planetary Emulation Terrain 3D Mapping Dataset
  - Stanford 3D Scanning Repository
  - ISPRS Test On Extracting DEMs From Point Clouds
  - SmartMultiMedia LiDAR Software and Point Cloud Sample Data
  - Leica Geosystems (projected data)
  - Pseudo-Simulated LiDAR
  - Cyberware Head & Face Color 3D Scanner
  - Autodesk Labs
  - http://www.lidardata.com/
  - USGS Seamless Data Warehouse
  - USGS Historic DEMs
  - ASTER, JPL
  - USGS DEMs, geocomm
  - The Digital Michelangelo Project
  - The Chapel Hill Volume Rendering Test Data Set
  - Large Geometric Models Archive, Georgia Tech
  - Virtual Terrain Project (has links to several sources for data)
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Re: Clouds of points - where I can find?

hielsber

Since the last post, this has gone up as a news item to which there were several replies with additional links. I am hoping this eventually makes its way to a new page on the PCL site, but in the mean time here are the latest set of links. Thanks to Alexander Velizhev, François Pomerleau and Robert Huitl for their submissions.

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Re: Clouds of points - where I can find?

Radu B. Rusu
Administrator
Awesome work guys! We'll probably try to get this setup on the main website tomorrow.

In general, if anyone has any interesting announcements to make on the recently redesigned pointclouds.org News page,
please don't hesitate to contact one of the maintainers. Bloggers welcome! :)

Cheers,
Radu.
--
http://openperception.org

On 01/11/2013 05:43 PM, hielsber wrote:

> Since the last post, this has gone up as a news item to which there were
> several replies with additional links.  I am hoping this eventually makes
> its way to a new page on the PCL site, but in the mean time here are the
> latest set of links.  Thanks to Alexander Velizhev, François Pomerleau and
> Robert Huitl for their submissions.
>
>
> 3D Point Clouds
>        
>              
> Autodesk Research - Digital 210 King <http://www.digital210king.org>
>                   Sample scan and image data of the Autodesk Research office.                  
> Autonomous Systems Lab (ETH) <http://projects.asl.ethz.ch/datasets/>
>                   Laser and Kinect data from structured and unstructured
> environments.  This group has a list of useful related links as well as a
> similar set of  links to data.
> <http://projects.asl.ethz.ch/datasets/doku.php?id=related_links>                          
> Canadian Planetary Emulation Terrain 3D Mapping Dataset
> <http://asrl.utias.utoronto.ca/datasets/3dmap/>
>                   Laser scans of unstructured terrains from rover platforms.
> Includes Matlab code for data parsing.
> Leica Geosystems (projected data)
> <http://hds.leica-geosystems.com/en/Support-Downloads-Example-Databases_29453.htm>
>                   Example databases of laser scan data.
> Point Cloud Classification (Lomonosov Moscow State university)
> <http://graphics.cs.msu.ru/en/node/922>
>                   Aerial lidar data with class labeling.
> Pointools <http://www.pointools.com/download.php>
>                   Sample data sets for pointools evaluation.
> Pseudo-Simulated LiDAR <http://www.math.sc.edu/~hielsber/MOUT.htm>
>                   Pseudo-simulated lidar data created for change detection
> experiments.                        
> Robotic 3D Scan Repository
> <http://kos.informatik.uni-osnabrueck.de/3Dscans/>
>               Registered 3D scans of indoor and outdoor environments.  Some
> data sets include thermal and color information.            
> SmartMultiMedia LiDAR Software and Point Cloud Sample Data
> <http://www.smartmm.com/downloads.html>
>                   Sample LiDAR scan data sets, including links to commercial
> point cloud software.                        
>          
> Localization and Mapping
>        
>
> KITTI Vision Benchmark Suite
> <http://www.cvlibs.net/datasets/kitti/index.php>
>                   Mono and stereo camera data, including calibration,
> odometry and more.                  
> MIT DARPA Grand Challenge Team
> <http://grandchallenge.mit.edu/wiki/index.php?title=PublicData>
>                   Camera, lidar and log files, including source code for
> parsing logs.
> NAVVIS Indoor Dataset <http://navvis.de/dataset/>
>                   LIDAR scans of the interiors of the corridors of the TU
> Munich main campus, acquired slice-by-slice by a mapping trolley and
> aggregated into a big point cloud.  The site also includes registered
> imagery, camera calibration, occupancy grid maps and more.
> The New College Vision and Laser Data Set
> <http://www.robots.ox.ac.uk/NewCollegeData/>
>                   Stereo and omni-directional imagery, lidar and pose data.
> PeRL: Ford Campus Vision and Lidar Dataset
> <http://robots.engin.umich.edu/SoftwareData/Ford>
>                   Camera and lidar data, including source code and more.                
> Radish: The Robotics Data Set Repository <http://radish.sourceforge.net>
>                   Odometry, laser and sonar data, including log files and
> generated maps.                  
> SLAM-related robotics data sets (University of Freiburg)
> <http://www.informatik.uni-freiburg.de/~stachnis/datasets.html>
>                   Compilation of 2D maps in the form of raw and correct log
> files.
>          
> Models
>        
>              
> The Digital Michelangelo Project <http://graphics.stanford.edu/data/mich/>
>                   Data is free but must be ordered as it is quite large.
> Large Geometric Models Archive (Georgia Tech)
> <http://www.cc.gatech.edu/projects/large_models/>
>                   Collection of standard models.                      
> Stanford 3D Scanning Repository
> <http://graphics.stanford.edu/data/3Dscanrep/>
>                   Collection of standard models (bunny, dragon, etc)
> including range data and zippered reconstructions.
>          
> Heightmaps (DEM and similar)
>        
>              
> ASTER, JPL <http://asterweb.jpl.nasa.gov/gdem.asp>
>                   Global DEM.
> GNet <http://b5m.gipuzkoa.net/url5000/en/M_039/PUBLI>
>                   Large aerial lidar data set.                      
> ISPRS Test On Extracting DEMs From Point Clouds
> <http://www.itc.nl/isprswgIII-3/filtertest/>
>                   First and last pulse laser data from overhead scans of
> urban and natural environments.                        
> http://www.lidardata.com/ <http://www.lidardata.com/>
>                   Large database of aerial lidar.  Data sets must be ordered
> and may not be free.
> National Land Survey of Finland
> <https://tiedostopalvelu.maanmittauslaitos.fi/tp/kartta?lang=en>
>                   Elevation and similar data of Finland.
> OpenTopography <http://www.opentopography.org/data>
>                   Aerial lidar data.
> USGS DEMs, geocomm <http://data.geocomm.com/dem/demdownload.html>
>                   Data sets must be ordered and may not be free.              
> USGS Historic DEMs <http://ned.usgs.gov/Ned/historic.asp>
>                   Mount St. Helens DEMs before and after 1980 eruption.
> Possibly other free data sets.
> USGS Seamless Data Warehouse <http://seamless.usgs.gov/>
>                   Large database of topographic data from USGS and NGA.  Data
> sets must be ordered and may not be free.                                            
>          
> Face Scans
>        
>      
> Cyberware Head &amp; Face Color 3D Scanner
> <http://www.cyberware.com/products/scanners/pxSamples.html>
>                   Sample head and face data including original data, merged
> ply files and uv/color data.                                                        
>          
> Volume Data (MRI and similar)
>        
>                          
> The Chapel Hill Volume Rendering Test Data Set
> <http://education.siggraph.org/resources/cgsource/instructional-materials/archives/volume-visualization-data-sets>
>                   Head, knee and cadaver MRI data.                                                              
>          
> Object Detection
>        
>              
> B3DO: Berkeley 3D Object Dataset <http://kinectdata.com>
>                   Indoor object detection data sets.
> NYU Depth Datasets <http://cs.nyu.edu/~silberman/datasets/>
>                   Indoor object detection data sets.
> RGB-D Object Dataset <http://www.cs.washington.edu/rgbd-dataset/index.html>
>                   Indoor object detection data sets with many common
> household objects.
> Semantic Database of 3D Objects (Technische Universität München)
> <https://ias.cs.tum.edu/software/semantic-3d>
>                   Stereo camera and lidar scans of typical household objects.                                              
>          
> Misc/Variety
>        
>
> Computer Vision Group (Technische Universität München)
> <http://vision.in.tum.de/data/datasets>
> Kinect RGB-D data for visual SLAM, multiview 3D reconstruction data and
> other image based data sets.
> Virtual Terrain Project <http://vterrain.org/>
>                   3D LiDAR data, topographic and other data.  This site also
> has many useful links.                        
>        
>
>
>
>
> --
> View this message in context: http://www.pcl-users.org/Clouds-of-points-where-I-can-find-tp4025095p4025363.html
> Sent from the Point Cloud Library (PCL) Users mailing list mailing list archive at Nabble.com.
> _______________________________________________
> [hidden email] / http://pointclouds.org
> http://pointclouds.org/mailman/listinfo/pcl-users
>
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Re: Clouds of points - where I can find?

hielsber
Sounds good.  Just let us know when you are ready.  Also, I have a few links to sites with some useful software/tools.  Sasha also volunteered some links to tools as well.
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Re: Clouds of points - where I can find?

hielsber
In reply to this post by Radu B. Rusu
Radu,

I have updated the sample page for the links and have cc'd you on an email to Sasha.  Let me know if this is the direction you would like this to go.  

Yours,
Matt
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Re: Clouds of points - where I can find?

hielsber
Just to close out this thread.  A larger set of links for both data and available software has been added to http://pointclouds.org/media/.
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Re: Clouds of points - where I can find?

jotauve
In reply to this post by tstanley
Also, I have a repository with some PCL code and also a lot of pointclouds in PCD format of a previous work about object recognition:

https://github.com/jvgomez/irml/

Concretely https://github.com/jvgomez/irml/tree/master/pointclouds/database

The pointclouds are captured with the focus of segment objects and get many views of them.

I hope this can be useful :)

http://www.sgpsproject.org http://www.javiervgomez.com
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Re: Clouds of points - where I can find?

hielsber
I have added your links to the data and software sections.  Let me know if you have any updates or would like me to change the descriptions.

Thanks!
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Re: Clouds of points - where I can find?

ehomar@iri.upc.edu
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This post was updated on .
In reply to this post by tstanley
I have data set, and we have matlab code to convert the point clouds  to pcd.

http://www.iri.upc.edu/research/webprojects/pau/datasets/BRL/php/dataset.php
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Re: Clouds of points - where I can find?

hielsber
The link has been added to http://pointclouds.org/media/ under Localization and Mapping.

Thanks!