4D event imaging with a single neuromorphic camera

Neuromorphic cameras, or dynamic vision sensors, are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level. Recently, they garnered increasing interest due to their extremely high temporal resolution, wide dynamic range, low power consumption, and high pixel bandwidth. Despite their advantages, most existing three-dimensional (3D) event imaging solutions rely on multicamera configurations, which are costly, complex, and challenging to synchronize. In this study, we introduce a new framework for four-dimensional (4D) event imaging using a single static neuromorphic camera. We take advantage of the inherent sparsity of event data to combine optically encoded stereo channels into a single event camera. By utilizing optical channel multiplexing, we maintain sensor resolution while retaining the key advantages of event cameras.