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PCL and Dinast Code Sprint 2012


It is our immense pleasure to announce the beginning of a new PCL Code Sprint sponsored by DINAST: PCL-DINCS!

DINAST, a short range 3D sensor manufacturer known for their IPA infrared cameras, is looking for talented developers that are willing to contribute to two areas in PCL:

  1. a pcl::Grabber camera driver interface for DINAST cameras (standalone BSD open source C++ driver code already available);
  2. a technology demonstrator for real-time 3D collision mapping (e.g., using octree structures) used for motion planning with a mobile manipulator, using multiple IPA 3D cameras.

PCL-DINCS will run for 1.5 months during this summer. The student developer will receive a stipend of $1500 and several IPA 3D cameras. Potential candidates should submit the following information to

  • a brief resume
  • a list of existing PCL contributions (if any)
  • a list of projects (emphasis on open source projects please) that they contributed to in the past

This project requires good…

PCL goes Mobile with VES and Kiwi

The mobile revolution is upon us! Who says mobile platforms are only good for email and Facebook? Why not 3-D perception and scientific visualization? Today's phones and tablets ship with multi-core CPUs, gigabytes of RAM, and more pixels than you can see. If you want to run Point Cloud Library on your iPhone, then who's to stop you? Mobile is here.

The Point Cloud Library community, Willow Garage, NVidia and Kitware are pleased to announce their collaboration to bring point cloud visualization to the mobile domain. You don't have to stop at visualization either; why not run a couple of PCL filters on your device while you're at it? Development sponsored by the NVidia Code Sprint has brought examples of point cloud streaming mobile clients, apps that read PCD files and execute PCL filters, and point cloud visualizations with millions of points.

Kiwi_logo Vtk logo Android logo Ios logo Kitware logo

Google Summer of Code 2012 ready to begin!

We have used all the 11 slots that Google allocated to our organization, gathering a veritable dream-team of researchers and coders from all over the world:

  • Kripasindhu Sarkar from the Indian Institute of Technology, Kharagpur is a senior undergraduate who is going to work on 2D Image Drawing Operators from VTK in PCL, under the supervision of:
    • Marcus Hanwell
    • Pat Marion
  • Yangyan Li, PhD student from the Visual Computing Research Center(VCC), Shenzhen Institutes of Advanced Technology(SIAT), Chinese Academy of Sciences is tackling a project he proposed himself, called ScanModeler: a Point Cloud based Reconstruction Platform, being helped out by:
    • Stefan Holzer
    • Federico Tombari
  • Changhyun Choi is a graduate student from Georgia Institute of Technology, Atlanta, Georgia, USA, and will be developing algorithms for 3D edge extraction from an organized point cloud, mentored by:
    • Alex Trevor
  • Gioia Ballin recently graduated magna cum laude her MSc from University of Padua, Italy, and proposed to work on Additional functionalities and improvements for PCL modules, such as new feature descriptors and increments to the recognition…

First PCL Code Sprint - TOCS - a success !

We are proud to announce that the first ever PCL code sprint has recently ended, with the submission of the final reports.

More details about what they have contributed with during this period, and the final reports can be found on the TOCS developer's blog:

We are now…

New Object Segmentation Algorithms

There are several tools available in PCL trunk that may be useful to the upcoming mobile manipulation challenge. Tools for segmentation of organized point cloud data (as from a Kinect or Xtion) have been added in pcl::OrganizedConnectedComponentSegmentation and pcl::OrganizedMultiPlaneSegmentation. These can be used for fast segmentation of all planes in the scene or euclidean clustering. It can also be extended with your own comparison functions for other segmentation tasks.

An example of how to use the plane segmentation is:

// Segment planes
pcl::OrganizedMultiPlaneSegmentation< PointT, pcl::Normal, pcl::Label > mps;
mps.setMinInliers (10000);
mps.setAngularThreshold (0.017453 * 2.0); // 2 degrees
mps.setDistanceThreshold (0.02); // 2cm
mps.setInputNormals (normal_cloud);
mps.setInputCloud (cloud);
std::vector< pcl::PlanarRegion< PointT > > regions;
mps.segmentAndRefine (regions);

for (size_t i = 0; i < regions.size (); i++)
  Eigen::Vector3f centroid = regions[i].getCentroid ();
  Eigen::Vector4f model = regions[i].getCoefficients ();
  pcl::PointCloud boundary_cloud;
  boundary_cloud.points = regions[i].getContour ();
  printf ("Centroid: (%f, %f, %f)\n  Coefficients:…

PCL-NVCS kickstart!

PCL-NVCS is ready to start! The sprint will cover 3D algorithmic work for human body recognition, deformable object modeling, and real-time visualization on Tegra3 platforms. Here's a list of the PCL developers working on the sprint:

  • Pat Marion, a member of the scientific visualization group at Kitware, will be working on point cloud streaming to Tegra3 devices for mobile visualization. Pat brings in years of experience by having had worked on large 3D visualization engines such as VTK, ParaView, and VES.
  • Koen Buys from Katholieke Universiteit Leuven, will be working on human body tracking from point cloud data. Koen is already a PCL developer and has been working on body tracking using GPUs as part of his doctoral research.
  • Martin Saelzle from Technische Universitaet Muenchen, will be working on deformable object modeling for PCL. Martin acquired extensive experience in point cloud registration using Kinect sensors while working in Prof. Nassir Navab's group at TUM.

We would like to thank all the other candidates for their excellent proposals! We already started…

PCL - Google Summer of Code 2012

We are very proud to announce that the Point Cloud Library has been accepted for the second time in the Google Summer of Code program. This is a great opportunity to have new people joining the thriving community of open-source 3D perception.

The webpage where you will find our list of ideas We are very flexible with the project ideas, and we are accepting interesting and solid (!!!) project proposals on our official event mailing list: or for more direct communication on IRC:, channel #pcl.

In order to apply, please follow the instruction on the official GSoC website and our custom student application requirements.

PCL-SRCS kickstart!

PCL-SRCS is ready to start! The sprint will cover 3D algorithmic work for surface reconstruction and large scale mapping for PCL. Our developers are:

PCL-HRCS kickstart!

PCL-HRCS is ready to start! The two developers that will be working on 3D technologies for driver-assistance systems are:

  • Aitor Aldoma, from Vienna University of Technology, will be working on 3D face orientation. Aitor has been working on techniques for object recognition and 6DOF pose alignment out of point cloud data for PCL in the past, such as CVFH.
  • Alex Trevor, from Georgia Institute of Technology, will be working on non-ground extraction from point cloud data. Alex has developed various real-time segmentation methods for planar components as part of PCL.

We would like to thank all the other candidates for their excellent proposals! We already started following up with each of them individually, as there are many more sprints to come!

[Note: the new blogging page for HRCS will be up within the next few days at]

PCL and Sandia Robotics Code Sprint 2012

Sandia Robotics

It is our immense pleasure to announce the beginning of a new PCL Code Sprint sponsored by Sandia Robotics group: PCL-SRCS!

PCL Code Sprints are intended to rapidly advance the capabilities of the Point Cloud Library in a certain area/subject by offering stipends to talented student developers and pairing them with knowledgeable mentors for several months of accelerated software development. Projects will run for an initial period of 3 months, and all of the code produced will be BSD-licensed open source.

For this spring's PCL-Sandia Robotics Code Sprint, we have identified the following important areas for further development in PCL, and we are therefore searching for outstanding candidates (and mentors) to work on the following projects:

  1. Kinect Fusion extensions to large scale environments: the purpose of this project is to extend techniques such as Kinect Fusion to larger scale environments with CUDA. A goal would be to combine it with a segmentation algorithm in order to be able to create specific object models. CUDA/GPGPU programming knowledge is…

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