GIPS: Geometry-Inspired Passive ToF Sensing for 3D Depth Reconstruction

The motivation for this work lies in the ubiquitous lighting infrastructure that surrounds us, which has been repurposed as a medium for optical wireless communication (OWC). This technology has enabled the development of passive 3D imaging. However, the fundamental problem with passive Time-of-Flight (ToF) imaging is the unknown source location, which generates a chicken and egg problem that renders passive ToF unusable in practice. In this work, we propose computational methods to solve this problem. We present a novel algorithm with a gradient descent approach for jointly estimating the source location and retrieving the correct depth information of the scene. In each iteration, the bistatic configuration is used as a basic framework while seeking local planarity to constrain the source location. The performance of our algorithm is evaluated in terms of source location estimation error and depth reconstruction error for two usual plane orientations through numerical simulations. Simulation results confirm the ability of the method to jointly retrieve the scene depth and source location. This work has huge potential for next-generation wireless networks, e.g., 6G, and paves the way towards 3D reconstruction in multiple practical applications.