  Optical Flow (OF) is the movement pattern of pixels or edges that is caused
in a visual scene by the relative motion between an agent and a scene. OF is
used in a wide range of computer vision algorithms and robotics applications.
While the calculation of OF is a resource-demanding task in terms of
computational load and memory footprint, it needs to be executed at low
latency, especially in robotics applications. Therefore, OF estimation is today
performed on powerful CPUs or GPUs to satisfy the stringent requirements in
terms of execution speed for control and actuation. On-sensor hardware
acceleration is a promising approach to enable low latency OF calculations and
fast execution even on resource-constrained devices such as nano drones and
AR/VR glasses and headsets. This paper analyzes the achievable accuracy, frame
rate, and power consumption when using a novel optical flow sensor consisting
of a global shutter camera with an Application Specific Integrated Circuit
(ASIC) for optical flow computation. The paper characterizes the optical flow
sensor in high frame-rate, low-latency settings, with a frame rate of up to 88
fps at the full resolution of 1124 by 1364 pixels and up to 240 fps at a
reduced camera resolution of 280 by 336, for both classical camera images and
optical flow data.
