Published September 21, 2020 | Version 1.0.0
Dataset Open

Event-Based Visual Place Recognition With Ensembles of Temporal Windows

  • 1. Queensland University of Technology

Description

This dataset accompanies the following publication, please cite this publication if you use this dataset:

Fischer, T. and Milford, M., 2020. Event-Based Visual Place Recognition With Ensembles of Temporal Windows. IEEE Robotics and Automation Letters5(4), pp.6924-6931.

@article{fischer2020event,
  title={Event-Based Visual Place Recognition With Ensembles of Temporal Windows},
  author={Fischer, Tobias and Milford, Michael},
  journal={IEEE Robotics and Automation Letters},
  volume={5},
  number={4},
  pages={6924--6931},
  year={2020}
}

The dataset contains six sequences of recordings. For each recording, four files are made available:

  1. A rosbag (*.bag) file with the following contents:
    • /dvs/events (type: dvs_msgs/EventArray) with the event stream, see https://github.com/uzh-rpg/rpg_dvs_ros)

    • /dvs/camera_info (type: sensor_msgs/CameraInfo) with the camera info of the DAVIS frame camera

    • /dvs/image_raw (type: sensor_msgs/Image) with the DAVIS frame camera images

    • /dvs/imu (sensor_msgs/Imu) with the IMU data of the event camera

  2. An associated *_hot_pixels.txt file that contains the hot pixels for that recording (detected with https://github.com/cedric-scheerlinck/dvs_tools/tree/master/dvs_hot_pixel_filter)

  3. The recordings using a frame-based consumer camera (*.mp4 files)

  4. Associated GPS information (*.nmea) files recorded using the consumer camera - synchronized with the mp4 files.

 

Note that the timestamps of the event files and frame-based camera files do not match as they were not synchronized during recording time. Please see the associated code repository (https://github.com/Tobias-Fischer/ensemble-event-vpr) for the correct mappings and time offsets between the event recordings and frame-based recordings.

The code repository also contains code to match GPS data between different traverses.

Notes

This work received funding from the Australian Government, via grant AUSMURIB000001 associated with ONR MURI grant N00014-19-1-2571. The authors acknowledge continued support from the Queensland University of Technology (QUT) through the Centre for Robotics.

Files

20200421_170039-sunset1_concat.mp4

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Additional details

References

  • Fischer, T. and Milford, M., 2020. Event-Based Visual Place Recognition With Ensembles of Temporal Windows. IEEE Robotics and Automation Letters, 5(4), pp.6924-6931.