Abstract
Feature-based methods are a popular method for camera state estimation using event cameras. Due to the spatiotemporal nature of events, all event images exhibit smearing of events analogous to motion blur for a camera under motion. As such, events must be motion compensated to derive a sharp event image. However, this presents a causality dilemma where motion prior is required to unsmear the events, but a sharp event image is required to estimate motion. While it is possible to use the IMU to develop motion prior, it has been shown that the limited dynamic range of \pm \mathbf{2000}^{\circ}/\mathrm{s} is insufficient for high angular rate rotorcrafts. Furthermore, smoothing of motion-compensated images due to actual event detection time latency in event cameras severely limits the performance of feature-based methods at high angular rates. This paper proposes a Fourier-based angular rate estimator capable of estimating angular rates directly on non-motion compensated event images. This method circumvents the need for external motion priors in camera state estimation and sidesteps problematic smoothing of features in the spatial domain due to motion blur. Lastly, using an NVIDIA Jetson Xavier NX, the algorithm is demonstrated to be real-time performant up to 3960°/s.