3-D Point Cloud Dataset - CVPR 2009 subset
This repository contains labeled 3-D point cloud laser data collected from a moving
platform in a urban environment. Data are provided for research
Please submit questions or comments to Nicolas Vandapel
This data set was used to produce the results presented in our CVPR
2009 paper [project page].
If you use the data, please reference the following publication:
Contextual Classification with Functional
Max-Margin Markov Networks.
Daniel Munoz, J. Andrew (Drew) Bagnell, Nicolas
Vandapel, and Martial Hebert.
IEEE Computer Society Conference on Computer Vision
and Pattern Recognition (CVPR), June, 2009.
The data was collected using Navlab11 equiped with side looking SICK
LMS laser scanners and used in push-broom. The data was collected
around CMU campus in Oakland, Pittsburgh, PA.
Data are provided in ascii format: x y z label confidence, one point
per line, space as separator. Corresponding vrml files (*.wrl) and
label counts (*.stats) are also provided. The data set is made of two
subset (part2, part3) with each its own local reference frame, where
each file contains 100,000 3-D points. The training/validation and
testing data was filtered and labeled remapped from 44 into 5 labels [TXT].
||17 files, 1.6 millions 3-D pts, 44
||1 file, 36932 3-D pts, 5 labels
||1 file, 91579 3-D pts, 5 labels
||15 files, 1.3 millions 3-D pts, 5 labels
Prepared through collaborative participation in the Robotics consortium
sponsored by the U.S Army Research Laboratory under the Collaborative
Technology Alliance Program, Cooperative Agreement DAAD19-01-209912.