  In digital cameras, we find a major limitation: the image and video form
inherited from a film camera obstructs it from capturing the rapidly changing
photonic world. Here, we present vidar, a bit sequence array where each bit
represents whether the accumulation of photons has reached a threshold, to
record and reconstruct the scene radiance at any moment. By employing only
consumer-level CMOS sensors and integrated circuits, we have developed a vidar
camera that is 1,000x faster than conventional cameras. By treating vidar as
spike trains in biological vision, we have further developed a spiking neural
network-based machine vision system that combines the speed of the machine and
the mechanism of biological vision, achieving high-speed object detection and
tracking 1,000x faster than human vision. We demonstrate the utility of the
vidar camera and the super vision system in an assistant referee and target
pointing system. Our study is expected to fundamentally revolutionize the image
and video concepts and related industries, including photography, movies, and
visual media, and to unseal a new spiking neural network-enabled speed-free
machine vision era.
