This page contains high-quality stereo sequences recorded from a moving vehicle in Karlsruhe. The sequences, which are captured by Pointgrey Flea2 firewire cameras, are saved as rectified images in *.png format, ground truth odometry from an OXTS RT 3000 GPS/IMU system is provided in a separate text file.

The calibration files contain parameters of the system before and after rectification. You only need to consider the matrices P1_roi (left camera) and P2_roi (right camera), which represent the 3x4 projection matrices (P=K[R|t]) of the visible region of interest after rectification in row-aligned order, i.e., the first 4 entries are the first row, etc. The (intrinsic) calibration matrices K1 and K2 of the left and right camera are equal and specified by the first 3x3 submatrix of P1_roi and P2_roi, respectively. The left camera is the reference camera. Hence, the baseline is given by base = -P2_roi(1,4)/P2_roi(1,1). Reprojection to 3D can be performed via

X = (u-cu)*base/d
Y = (v-cv)*base/d
Z = f*base/d

where (u,v) is a 2D point in the image coordinate system, (cu,cv) is the principal point of the camera, f is the focal length, base is the baseline, d is the disparity and (X,Y,Z) is a 3D point in the camera coordinate system.

The file insdata.txt contains for each frame (first row = frame 0) the output from the GPS/IMU system. The columns are: timestamp,lat,lon,alt,x,y,z,roll,pitch,yaw. Here x,y,z is metric (z is the vehicle height over sea level), and can be used for comparing visual odometry, but make sure to align the rotation of both coordinate systems, and be aware that the GPS/IMU system is not as accurate as it is supposed to be (0.05 meters). The camera is roughly located 1.6 meters in front, 0.6 meters above and 0.05 meters to the left of the GPS/IMU system. The pitch angle of the camera with respect to the GPS/IMU is -0.08 radian or -4.6 degrees (the camera is slightly facing downwards).

Note: Unfortunately our recording program had a bug at the time of recording the sequences, so roll and pitch are not valid at the moment. We have fixed that bug, so that future sequences (especially those of the KITTI Vision Benchmark Suite) will be ok. The rest of the variables is correct, however. Thanks to Diego Rodriguez for reporting this issue!
Note: Also try our novel KITTI dataset here!
All datasets on this page are published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License.
If you find this dataset useful or if you use this software for your research, we would be happy if you cite the following related publications:

@inproceedings{Geiger2011IV,
  author = {Andreas Geiger and Julius Ziegler and Christoph Stiller},
  title = {StereoScan: Dense 3D Reconstruction in Real-time},
  booktitle = {Intelligent Vehicles Symposium (IV)},
  year = {2011}
}
@inproceedings{Geiger2010ACCV,
  author = { GeigerandAndreas and RoserandMartin and UrtasunandRaquel},
  title = {Efficient Large-Scale Stereo Matching},
  booktitle = {Asian Conference on Computer Vision (ACCV)},
  year = {2010}
}