  We propose a novel method for continuous-time feature tracking in event
cameras. To this end, we track features by aligning events along an estimated
trajectory in space-time such that the projection on the image plane results in
maximally sharp event patch images. The trajectory is parameterized by $n^{th}$
order B-splines, which are continuous up to $(n-2)^{th}$ derivative. In
contrast to previous work, we optimize the curve parameters in a sliding window
fashion. On a public dataset we experimentally confirm that the proposed
sliding-window B-spline optimization leads to longer and more accurate feature
tracks than in previous work.
