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Vision meets Robotics: The {KITTI} Dataset





We present a novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research. In total, we recorded 6 hours of traffic scenarios at 10-100 Hz using a variety of sensor modalities such as high-resolution color and grayscale stereo cameras, a Velodyne 3D laser scanner and a high-precision GPS/IMU inertial navigation system. The scenarios are diverse, capturing real-world traffic situations and range from freeways over rural areas to inner-city scenes with many static and dynamic objects. Our data is calibrated, synchronized and timestamped, and we provide the rectified and raw image sequences. Our dataset also contains object labels in the form of 3D tracklets and we provide online benchmarks for stereo, optical flow, object detection and other tasks. This paper describes our recording platform, the data format and the utilities that we provide.

Author(s): Andreas Geiger and Philip Lenz and Christoph Stiller and Raquel Urtasun
Journal: International Journal of Robotics Research
Volume: 32
Number (issue): 11
Pages: 1231 - 1237
Year: 2013
Month: September
Publisher: Sage Publishing

Department(s): Autonomous Vision, Perceiving Systems
Bibtex Type: Article (article)
Paper Type: Journal

DOI: 10.1177/0278364913491297

Links: pdf


  title = {Vision meets Robotics: The {KITTI} Dataset},
  author = {Geiger, Andreas and Lenz, Philip and Stiller, Christoph and Urtasun, Raquel},
  journal = {International Journal of Robotics Research},
  volume = {32},
  number = {11},
  pages = {1231 - 1237 },
  publisher = {Sage Publishing},
  month = sep,
  year = {2013},
  month_numeric = {9}