Before revision:  Conversely, conventional image sensors measure absolute intensity of slowly changing scenes effectively but do poorly on quickly changing scenes with high dynamic range . The proposed approach exploits advantages of hybrid sensors under a unifying uncertainty model for both conventional frames and events.
After revision:  Conversely, conventional image sensors measure absolute intensity of slowly changing scenes effectively but do poorly on quickly changing scenes with high dynamic range or quickly changing scenes. In this paper, we present an event-based video reconstruction pipeline for High Dynamic Range (HDR) scenarios. The proposed algorithm includes a frame augmentation pre-processing step that deblurs and temporally interpolates frame data using events. The augmented frame and event data are then fused using a novel asynchronous Kalman filter under a unifying uncertainty model for both conventional frames and events.