For academic use only.
Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception
Ziwei Wang, Liyuan Pan, Yonhon Ng, Zheyu Zhuang and Robert Mahony
The paper was accepted by the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021) in Prague, Czech Republic.
Publications
@inproceedings{wang2021stereo, title={Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception}, author={Wang, Ziwei and Pan, Liyuan and Ng, Yonhon and Zhuang, Zheyu and Mahony, Robert}, booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year={2021}, organization={IEEE} }
IROS-video
https://www.youtube.com/watch?v=Azu7rJSPGNc
Data
Events Image Raw Data:
Three scenarios: picnic, complex boxes, and simple boxes. Each scenario includes at least 6 sequences with different camera speeds and lighting conditions.
From FLIR RGB camera | From Prophesee event camera | Description | |
---|---|---|---|
Intensity images | yes | no | Synchronised intensity images from FLIR RGB camera |
images_ts.txt | no | yes | Timestamps of the ynchronised intensity images. We synchronise the two cameras by sending a trigger signal from the FLIR RGB camera to the event camera. |
log_td.dat | no | yes | Event data, includes event x, y, ts, p |
Notes:
Events are decompressed from .raw to .dat format. To convert raw data to .dat or .csv format, we used the Prophesee tools in Prophesee_tools You can also install the last Prophesee software version follow the instructions on the website If you need, you can find all tools in /usr/share/prophesee_driver/samples or /usr/share/metavision/sdk/driver/samples, depending on what version you are using.
Processed stereo event-frame dataset
Parameters for each sequence
Stereo hybrid event-frame calibration data
Point cloud
UR5 robot arm pose
Notes
- If you have any questions regarding this code and the corresponding results, please contact [email protected]