ABSTRACT
Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called ‘events’. Event cameras offer advantages over conventional frame-based cameras in terms of latency, high dynamic range (HDR) and temporal resolution. Event cameras do not output conventional image frames, thus, image reconstruction from events enables visualisation and frame-based processing. Convolution is a fundamental tool for computer vision, however, its application to event cameras is unclear. We show how to compute convolution event-by-event. Until recently, event cameras have been limited to grayscale intensity. Now, a new color event camera is available and we unveil the color information contained in events by reconstructing color images, and release the Color Event Camera Dataset.