Abstract. In this work, we propose a novel event based stereo method
which addresses the problem of motion blur for a moving event camera.
Our method uses the velocity of the camera and a range of disparities
to synchronize the positions of the events, as if they were captured at
a single point in time. We represent these events using a pair of novel
time synchronized event disparity volumes, which we show remove motion blur for pixels at the correct disparity in the volume, while further
blurring pixels at the wrong disparity. We then apply a novel matching
cost over these time synchronized event disparity volumes, which both
rewards similarity between the volumes while penalizing blurriness. We
show that our method outperforms more expensive, smoothing based
event stereo methods, by evaluating on the Multi Vehicle Stereo Event
Camera dataset