EE3P: Event-based Estimation of Periodic Phenomena Properties

TL;DR

This paper presents EE3P, a contactless event camera-based method for accurately estimating properties of periodic phenomena like light flashes, vibration, and rotation, achieving less than 0.04% error.

Contribution

It introduces a novel correlation-based approach for frequency estimation using event cameras, eliminating the need for markers or landmarks.

Findings

Achieves less than 0.04% relative error in experiments

Works effectively for light flashes, vibration, and rotational speed

Eliminates the need for markers or distinguishable landmarks

Abstract

We introduce a novel method for measuring properties of periodic phenomena with an event camera, a device asynchronously reporting brightness changes at independently operating pixels. The approach assumes that for fast periodic phenomena, in any spatial window where it occurs, a very similar set of events is generated at the time difference corresponding to the frequency of the motion. To estimate the frequency, we compute correlations of spatio-temporal windows in the event space. The period is calculated from the time differences between the peaks of the correlation responses. The method is contactless, eliminating the need for markers, and does not need distinguishable landmarks. We evaluate the proposed method on three instances of periodic phenomena: (i) light flashes, (ii) vibration, and (iii) rotational speed. In all experiments, our method achieves a relative error lower than 0.04%, which is within the error margin of ground truth measurements.