Feedback control of event cameras
This work addresses the need for automatic parameter adjustment in event cameras, which is incremental as it introduces basic feedback control methods.
The paper tackles the problem of manually tuning bias parameters in event cameras by proposing fixed-step feedback controllers that automatically regulate event rate and noise, demonstrating model validity and feedback control in experiments.
Dynamic vision sensor event cameras produce a variable data rate stream of brightness change events. Event production at the pixel level is controlled by threshold, bandwidth, and refractory period bias current parameter settings. Biases must be adjusted to match application requirements and the optimal settings depend on many factors. As a first step towards automatic control of biases, this paper proposes fixed-step feedback controllers that use measurements of event rate and noise. The controllers regulate the event rate within an acceptable range using threshold and refractory period control, and regulate noise using bandwidth control. Experiments demonstrate model validity and feedback control.