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ablation_study_components/fast/1/aps/frames/ab_h_qry/1710350206934273
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End of preview.
Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras
Welcome to the official QCR-Fast-Slow-Event-Dataset dataset repository attached to the paper Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras, to be presented at the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024). This work introduces feedback control algorithms that dynamically change bias parameters for event-cameras to stabilize event-rate in an online manner. The work reports improvements in visual place recognition performances across variations in environment brightness conditions, validated through comprehensive real-time evaluations using a new QCR-Fast-and-Slow-Event-Dataset.
File Structure
QCR-Fast-Slow-Event-Dataset
├── ablation_study_components.tar.gz
├── ablation_study_slow_changes_freq.tar.gz
├── grid_search
│ ├── aedats
│ │ ├── +0+0+0_h_qry.aedat.tar.gz
│ │ ├── ...
│ │ ├── ... (Raw AEDAT2.0's from 108 traversals)
│ │ ├── ...
│ │ └── -2-2-2_l_ref.aedat.tar.gz
│ └── bags.tar.gz
├── main_experiments
│ ├── default_params.tar.gz
│ ├── Fast_Slow.tar.gz
│ ├── PxBw.tar.gz
│ ├── PxTh.tar.gz
│ └── RfPr.tar.gz
└── README.md
More information on how to use the dataset can be found in the official codebase repository on GitHub.
Cite us at
Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras
@inproceedings{nair2024enhancing,
title={Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras},
author={Nair, Gokul B and Milford, Michael and Fischer, Tobias},
booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
year={2024}
}
License
This dataset is licensed under the MIT License.
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