DAViS Camera Optical Flow

Abstract

Frame-based optical flow (OF) methods struggle in the presence of large motion and occlusion due to slow frame rates. Optical flow of dynamic vision sensor (DVS) has gained attention recently as a way to overcome these shortcomings. DVS reports “events” corresponding log intensity changes exceeding a specific threshold, with an accuracy of microsecond order. The increased temporal sampling rate are indeed helpful, but the poor spatial fidelity of DVS outputs make events-based OF less reliable overall. In this work, we consider a new sensor called DAViS that combines the conventional active pixel sensor (APS) and DVS circuitries, yielding a conventional intensity image frames as well as the events. We propose a novel optical flow method designed specifically for a DAViS camera that leverages the high spatial fidelity of intensity image frames and the high temporal resolution of events generated by DVS. Hence, the proposed DAViS-OF method yields reliable motion vector estimates while overcoming the fast motion and occlusion problems. The proposed DAViS-OF method is computationally efficient and is suitable for real-time implementation.