Measuring artificial raindrop diameters and velocities with a neuromorphic event camera
Embedded Files
This page points to photos, videos, code and data associated with the following paper: "Measuring Diameters and Velocities of Artificial Raindrops with a Neuromorphic Event Camera" reports a novel rain droplet measurement method (a disdrometer method) that uses a neuromorphic event camera to measure droplet sizes and speeds as they fall through a shallow plane of focus.
Using our new hard disk drive droplet generator, our experimental results show accuracy and precision similar to a commerical PARSIVEL laser sheet disdrometer.
Because these measurements are driven by event camera activity, this approach could enable economical deployment of ubiquitous networks of solar-powered disdrometers, which are critical for measuring the droplet size distribution to accurately estimate rainfall water volume from radar measurements.
Developed by collaboration between the Sensors Group of the Inst. of Neuroinformatics, Univ. of Zurich and ETH Zurich and the Swiss Federal Institute of Aquatic Science and Technology.
Citation
Citation
Micev, Kire, Jan Steiner, Asude Aydin, Jörg Rieckermann, and Tobi Delbruck. 2024. “Measuring Diameters and Velocities of Artificial Raindrops with a Neuromorphic Event Camera.” Atmospheric Measurement Techniques. doi:10.5194/amt-17-335-2024. https://amt.copernicus.org/articles/17/335/2024/
Article received 9 Feb 2023, Discussion started 17 Apr 2023, revised 22 Sept 23, accepted 31 Oct 2023, published 18 Jan 2024. at Atmosphere Measurement Technology at https://egusphere.copernicus.org/preprints/2023/egusphere-2023-215/#discussion
We would appreciate citations if using data from this site.
Summary of methods
Summary of methods
Summary of results
Summary of results
Acknowledgements
Acknowledgements
We thank J.P. Carbajal (Ostschweizer Fachhochschule) for catalyzing this collaboration, G. Taverni (formerly UZH-ETH, now see her linked in profile) for help with initial feasibility studies, S. Kosch (aldusleaf.org), N. Ashgriz (U. Toronto), and R. Loidl (UZH-ETH) for their advice on building the droplet generator. We thank Prof. Konrad Schindler for supervision of Kire and Jan during their bachelor project work.
Information about other datasets and tools are on the Sensors Group webpage.
Page updated
Google Sites
Report abuse