When: July 1, 2011
Where: Robotics: Science and Systems (RSS) 2011, University of Southern California, in Los Angeles, California, USA.
With the advent of new, low-cost hardware such as OpenNI compatible cameras and continued efforts in advanced open source 3D point cloud processing, 3D perception gains more and more importance in robotics, as well as other fields. The workshop attempts to motivate new developers and ideas to delve into this subject by offering a tutorial on point cloud processing using the emerging Point Cloud Library (PCL), which presents an advanced and extensive approach to the subject, as well as providing an overview of existing systems applying these techniques. Our goal is to provide an excellent reference material for students and researchers interested in this subject and take our guests through a complete application demonstration (given live) that combines subjects such as filtering, feature estimation, segmentation, registration, object recognition and finally surface reconstruction. The tutorial will be held using OpenNI compatible sensors, so we encourage the audience to bring theirs so we can follow all the steps together. We're assembling a great list of invited speakers that will talk about the usage of PCL in their work and show impressive demos.
List of speakers:
|09:00 - 09:10||Welcome||Introductions + solve basic technical problems|
|09:10 - 09:40||Introduction||Radu B. Rusu|
|09:40 - 10:00||PCL I/O (code)||Nico Blodow and Suat Gedikli[*]|
Learning the PCD format and the Grabber interface.
|10:00 - 10:30||PCL Visualization (part 1, part 2)||Radu B. Rusu and Bastian Steder|
How to display your data on screen.
|10:30 - 10:45||Coffee & cookies|
|10:45 - 11:00||PCL Filters (I)||Radu B. Rusu|
Filtering your data: outliers vs inliers.
|11:00 - 11:30||PCL Segmentation + Filters (II) (code)||Nico Blodow|
Segmenting geometric primitives.
The SAmple Consensus (SAC) framework.
|11:30 - 11:45||Invited talk||Adam Leeper, Stanford University|
Telemanipulation using PCL
|11:45 - 12:15||PCL Keypoints and Features (code)||Michael Dixon and Radu B. Rusu|
How to estimate 3D features.
|12:15 - 13:30||Lunch|
|13:30 - 14:00||PCL Search||Marius Muja, Julius Kammerl[*]|
KdTrees and Octrees in PCL.
Change detection. Point cloud compression.
|14:00 - 14:20||Invited talk||Nico Blodow and Radu B. Rusu|
Technology preview: PCL on CUDA
|14:20 - 14:45||PCL Range Images||Bastian Steder|
Compact range image representations.
NARF keypoints and features. Object recognition using NARF.
|14:45 - 15:00||Invited talk||Michael Ruhnke, University of Freiburg|
Sparse Surface Adjustment - Joint Optimization of Sensor Poses and Surface Points
|15:00 - 15:30||Coffee & cookies|
|15:30 - 16:10||PCL Registration (code)||Jochen Sprickerhof, Dirk Holz[*], Michael Dixon|
How to align scans in a SLAM framework.
Creating 3D object models. Mapping.
|16:10 - 16:40||PCL Surface||Zoltan-Csaba Marton|
Creating surface meshes from point clouds
VFH cluster recognition
|16:40 - 17:00||Join Us!||Radu B. Rusu|
Before the tutorial starts, please make sure that: