Key points are not available for this paper at this time.
Neuromorphic sensors (also known as event based cameras) behave differently than traditional imaging sensors as they respond only to changes in stimuli as they occur. They typically have higher dynamic range and frame rates than traditional imaging systems while using less power than other imaging systems because a pixel only outputs data when a stimulus occurs at that pixel. There are a variety of uses for neuromorphic sensors from temporal anomaly detection to autonomous driving. While the information in the output of the neuromorphic sensor correlates to a change in stimuli, there has not been a defined means to characterize neuromorphic sensors in order to predict performance from a given stimuli. This study focuses on the measurement of the temporal and spatial response of a neuromorphic sensor with additional discussion on model performance based upon these measurements.
Burks et al. (Fri,) studied this question.