Event cameras are bio-inspired sensors providing significant advantages over
standard cameras such as low latency, high temporal resolution, and high
dynamic range. We propose a novel structured-light system using an event camera
to tackle the problem of accurate and high-speed depth sensing. Our setup
consists of an event camera and a laser-point projector that uniformly
illuminates the scene in a raster scanning pattern during 16 ms. Previous
methods match events independently of each other, and so they deliver noisy
depth estimates at high scanning speeds in the presence of signal latency and
jitter. In contrast, we optimize an energy function designed to exploit event
correlations, called spatio-temporal consistency. The resulting method is
robust to event jitter and therefore performs better at higher scanning speeds.
Experiments demonstrate that our method can deal with high-speed motion and
outperform state-of-the-art 3D reconstruction methods based on event cameras,
reducing the RMSE by 83% on average, for the same acquisition time.

使用事件相机的结构光系统通过优化空时一致性能量函数，可以更准确、快速地进行深度感知，相对于预言式算法可以更好地处理高速运动和降低误差。