pablovela5620/glide-slam-example

TUM RGB-D freiburg3_long_office_household — RGB only

A verbatim copy of one sequence of the TUM RGB-D benchmark, used as the sample input for the GLidE-SLAM pixi run demo task. It is mirrored here only so the demo can fetch a single sequence quickly; the authoritative copy is the one published by TUM.

Source

https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz

Contents

rgbd_dataset_freiburg3_long_office_household/
├── rgb/                 2585 PNG images, 640x480, 30 Hz
├── rgb.txt              timestamp <-> image path index
├── groundtruth.txt      motion-capture trajectory, TUM format (t tx ty tz qx qy qz qw)
└── accelerometer.txt    accelerometer log

The directory layout, the file names and the file contents are unchanged from the original archive.

The depth stream has been removed. GLidE-SLAM runs this sequence monocularly, so depth/ and depth.txt are not part of this mirror. Anyone who needs depth should take the original archive from the link above.

Camera

The sequence was recorded with a Kinect; the freiburg3 intrinsics are fx 535.4, fy 539.2, cx 320.1, cy 247.6, for 640x480 images.

License

CC BY 4.0, as published by the Computer Vision Group at TUM.

Citation

J. Sturm, N. Engelhard, F. Endres, W. Burgard and D. Cremers, "A Benchmark for the Evaluation of RGB-D SLAM Systems", Proc. of the International Conference on Intelligent Robot Systems (IROS), 2012.

@inproceedings{sturm12iros,
  author    = {J. Sturm and N. Engelhard and F. Endres and W. Burgard and D. Cremers},
  title     = {A Benchmark for the Evaluation of {RGB-D} {SLAM} Systems},
  booktitle = {Proc. of the International Conference on Intelligent Robot Systems (IROS)},
  year      = {2012}
}