Abstract:
##About Data collection site: New College, Oxford The New College Data Set contains 30GB of data intended for use by the mobile robotics and vision research communities. Our anticipated users are parties interested in outdoor 6 D.O.F. navigation and mapping (metric or topological) using vision and/or laser. ##Data Synopsis * Gathered while traversing 2.2km through a college's grounds and adjoining parks * 5 DOF dead reckoned pose at 28Hz * Stereo imagery captured at 20Hz * 5-view omni-directional images at 5Hz * range and intensity data from two vertically mounted SICK LMS 291-S14 lasers scanning at 75Hz ##Full Data Set Here we provide the data set in full. The data set consists of three streams of information: two sets of images, one from the Stereo Camera, and one from the Ladybug Camera, and an Alog file which contains other information like laser data and odometry. The image sets come in two formats. Firstly, we provide them as single zip files (via ftp) containing all the images. These are large files due to the number of images, so the second format is the image sets broken down into ~500MB chunks (via http). Image Sets, Multiple Zip Files * (http) Zipped Stereo Images (**) * (http) Zipped Ladybug Images * (http) Zipped Panorama Images(***) Alog File * (http) Alog File (220M) Visual Odometry Data [14-06-10] Please note that this data was not originally part of the IJRR submission. * (http) Visual Odometry (VO) data (7M) (**) Please note that the stereo images contain lens distortion and are unrectified. This makes them unsuitable for direct use in, for example, local window-based stereo matching. Code is provided that will perform undisortion and rectification on these image sequences. Download details and instructions for use are given: Code to undistort and rectify stereo image sequence. (***) Panoramas are provided as a quick overview of the ladybug image data. Each image is a concatenation of the 5 camera images, all captured at the same time. We suggest using the raw ladybug images as these correspond to the files referred to in the .alog file. ##Extracting Data From The Plain-text "alog files" All non-image data is stored in a plain-text log file called an "alog". To get acquainted with this format and suitable access methods we suggest you: 1. Download some data evaluation snippets, particularly the alog which is the text file containing all non-image data, and the Flash Laser Viewer. The data set is large and users may not wish to download 30G data and start using the parsing tools immediately so we have provided some short partitions of the alog file. 2. Download and compile (as a standalone executable or from within Matlab©) the alog parsing tool we provide called uAlogParser. Full instructions on how to compile this single source file on multiple platforms are given here. 3. Try running the parser on one of the smaller evaluation alog segments. If you have access to Matlab©, try running the point cloud builder on an evaluation chunk to see some 3D laser data. 4. Download the full alog file - perhaps after finding an event that appears interesting.
Year: 2009

URL: http://www.robots.ox.ac.uk/NewCollegeData/
License: No license specified, the work may be protected by copyright.

@article{,
title= {The New College Vision and Laser Data Set},
journal= {},
author= {Smith, M. and Baldwin, I. and Churchill, W. and Paul, R. and Newman, P.},
year= {2009},
url= {http://www.robots.ox.ac.uk/NewCollegeData/},
abstract= {##About 
Data collection site: New College, Oxford
The New College Data Set contains 30GB of data intended for use by the mobile robotics and vision research communities. Our anticipated users are parties interested in outdoor 6 D.O.F. navigation and mapping (metric or topological) using vision and/or laser.

##Data Synopsis
 * Gathered while traversing 2.2km through a college's grounds and adjoining parks
 * 5 DOF dead reckoned pose at 28Hz
 * Stereo imagery captured at 20Hz
 * 5-view omni-directional images at 5Hz
 * range and intensity data from two vertically mounted SICK LMS 291-S14 lasers scanning at 75Hz


##Full Data Set

Here we provide the data set in full. The data set consists of three streams of information: two sets of images, one from the Stereo Camera, and one from the Ladybug Camera, and an Alog file which contains other information like laser data and odometry. The image sets come in two formats. Firstly, we provide them as single zip files (via ftp) containing all the images. These are large files due to the number of images, so the second format is the image sets broken down into ~500MB chunks (via http).

Image Sets, Multiple Zip Files

 * (http) Zipped Stereo Images (**)

 * (http) Zipped Ladybug Images

 * (http) Zipped Panorama Images(***)

Alog File

 * (http) Alog File (220M)

Visual Odometry Data

[14-06-10] Please note that this data was not originally part of the IJRR submission. 

 * (http) Visual Odometry (VO) data (7M)


(**) Please note that the stereo images contain lens distortion and are unrectified. This makes them unsuitable for direct use in, for example, local window-based stereo matching. Code is provided that will perform undisortion and rectification on these image sequences. Download details and instructions for use are given: Code to undistort and rectify stereo image sequence.

(***) Panoramas are provided as a quick overview of the ladybug image data. Each image is a concatenation of the 5 camera images, all captured at the same time. We suggest using the raw ladybug images as these correspond to the files referred to in the .alog file.


##Extracting Data From The Plain-text "alog files"

All non-image data is stored in a plain-text log file called an "alog". To get acquainted with this format and suitable access methods we suggest you:

1. Download some data evaluation snippets, particularly the alog which is the text file containing all non-image data, and the Flash Laser Viewer. The data set is large and users may not wish to download 30G data and start using the parsing tools immediately so we have provided some short partitions of the alog file.
2. Download and compile (as a standalone executable or from within Matlab©) the alog parsing tool we provide called uAlogParser. Full instructions on how to compile this single source file on multiple platforms are given here.
3. Try running the parser on one of the smaller evaluation alog segments.
If you have access to Matlab©, try running the point cloud builder on an evaluation chunk to see some 3D laser data.
4. Download the full alog file - perhaps after finding an event that appears interesting.
},
keywords= {},
terms= {}
}