How Many Events Do You Need? Event-Based Visual Place Recognition Using Sparse But Varying Pixels

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

Fischer, T. and Milford, M., 2022. How Many Events Do You Need? Event-Based Visual Place Recognition Using Sparse But Varying Pixels. IEEE Robotics and Automation Letters, 7(4), pp.12275-12282.

@article{FischerRAL2022ICRA2023,

    title={How Many Events do You Need? Event-based Visual Place Recognition Using Sparse But Varying Pixels},

    author={Tobias Fischer and Michael Milford},

    journal={IEEE Robotics and Automation Letters},

    volume={7},

    number={4},

    pages={12275--12282},

    year={2022},

    doi={10.1109/LRA.2022.3216226},

}

The dataset contains seven sequences of recordings. For each recording, the following files are made available:

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

A parquet file that can be read with pandas, which is converted from the bag file, with a denoising algorithm applied.

A zip file containing the DAVIS frame camera images. Once extracted, the images have the timestamp as their filename.

Please see the associated code repository (https://github.com/Tobias-Fischer/sparse-event-vpr) for manually annotated ground-truth information.