High Speed Rotation Estimation with Dynamic Vision Sensors
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Abstract (arXiv)
Rotational speed is one of the important metrics to be measured for calibrating the electric motors in manufacturing, monitoring engine during car repairing, faults detection on electrical appliance and etc. However, existing measurement techniques either require prohibitive hardware (e.g., high-speed camera) or are inconvenient to use in real-world application scenarios. In this paper, we propose, EV-Tach, an event-based tachometer via efficient dynamic vision sensing on mobile devices. EV-Tach is designed as a high-fidelity and convenient tachometer by introducing dynamic vision sensor as a new sensing modality to capture the high-speed rotation precisely under various real-world scenarios. By designing a series of signal processing algorithms bespoke for dynamic vision sensing on mobile devices, EV-Tach is able to extract the rotational speed accurately from the event stream produced by dynamic vision sensing on rotary targets. According to our extensive evaluations, the Relative Mean Absolute Error (RMAE) of EV-Tach is as low as 0.03% which is comparable to the state-of-the-art laser tachometer under fixed measurement mode. Moreover, EV-Tach is robust to subtle movement of user's hand, therefore, can be used as a handheld device, where the laser tachometer fails to produce reasonable results.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 5 of its 33 references that are in the map. First posted on arXiv 6 Sep 2022.
Builds on
5 of 33 references.
References · 5
- 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
- 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
- 2019Event-based Vision: A Surveycited by 1,010
- 2018EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Camerascited by 223
- 2019Graph-Based Object Classification for Neuromorphic Vision Sensingcited by 85
Built on by
Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
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- 2026Event-Only Drone Trajectory Forecasting with RPM-Modulated Kalman Filteringcited by 1
- 2026Event-Only Drone Trajectory Forecasting with RPM-Modulated Kalman Filtering2 Mar 2026
- 2025Drone Detection with Event Cameras6 Aug 2025
- 2024EEPPR: Event-based Estimation of Periodic Phenomena Rate using Correlation in 3D13 Aug 2024
- 2024EE3P: Event-based Estimation of Periodic Phenomena Properties22 Feb 2024