What is different about this compared to just grabbing frames in software and differencing these frames? It sounds to me that doing it in hardware can give a performance improvement, but only a minor one.
This seems like one of those "obvious in hindsight" discoveries, which are always the best ones.
It's only really in the context of computer vision and object tracking that the brute force whole-frames model starts to seem less than convenient.
Yet, this also means the possibility of some missed changes, of some changes being taken as lighting changes, instead of object change.
Was that a cloud, or a large shape close to the lens?
Hmm. Gonna have to read on this.
Normal cameras lose information by accumulating the intensity of each pixel over time until the next frame "arrives". You can not reconstruct that information anymore by diffing the frame-based output.
Event cameras on the other hand track the timestamp of the intensity change for each pixel individually. Thus they experience far less motion blur because they don't average the signal amplitude over time.
However, I haven't yet understood why their dynamic range is also better.
If you’re sampling intensity changes at high frequency, then you don’t need to worry about saturating each pixel between each sample interval. Instead you would need to integrate over all the collected deltas to get an intensity value for a given time period.