The operation of the DVS event camera is controlled by the user through
adjusting different bias parameters. These biases affect the response of the
camera by controlling - among other parameters - the bandwidth, sensitivity,
and maximum firing rate of the pixels. Besides determining the response of the
camera to input signals, biases significantly impact its noise performance.
Bias optimization is a multivariate process depending on the task and the
scene, to which the user's knowledge about pixel design and non-idealities can
be of great importance.
In this paper, we go step-by-step along the signal pathway of the DVS pixel,
shining light on its low-level operation and non-idealities, comparing pixel
level measurements with array level measurements, and discussing and how
biasing and illumination affect the pixel's behavior. With the results and
discussion presented, we aim to help DVS users achieve more hardware-aware
camera utilization and modelling.Comment: Accepted at 2023 IEEE/CVF Conference on Computer Vision and Pattern
Recognition Workshops (CVPRW); 4th International Workshop on Event-Based
Visio