Contour motion estimation for asynchronous event-driven cameras

Francisco Barranco, Cornelia Fermuller, Yiannis Aloimonos

Abstract: This paper compares image motion estimation with asynchronous event-based cameras to Computer Vision approaches using as input frame-based video sequences. Since dynamic events are triggered at significant intensity changes, which often are at the border of objects, we refer to the event-based image motion as “contour motion.” Algorithms are presented for the estimation of accurate contour motion from local spatio-temporal information for two camera models: the dynamic vision sensor (DVS), which asynchronously records temporal changes of the luminance, and a family of new sensors which combine DVS data with intensity signals. These algorithms take advantage of the high temporal resolution of the DVS and achieve robustness using a multiresolution scheme in time. It is shown that, because of the coupling of velocity and luminance information in the event distribution, the image motion estimation …