GCSR: Gray Code Super-Resolution 3D Scanning

Digital pattern projectors used in structured light 3D scanners cannot project infinitesimally thin columns of light - the projector pixel columns have a finite thickness. Current methods incorrectly model these columns of light as planes, which contributes to reconstruction errors. We propose a method to increase the resolution of structured light 3D scanners based on time-multiplexed discrete patterns by taking multiple acquisitions of the scene with different projector poses, and by modeling the light projected by each pixel column as a volume in space instead of as a plane, which results in upper and lower bounds on the resulting depth map. Furthermore, by analyzing multiple acquisitions in different projector poses, these upper and lower depth bounds can be tightened. We refer to this tightening as super-resolution, because it corresponds to an increase in the confidence in the location of the object's surface. We describe our first implementation of such a system, and demonstrate its performance on a variety of objects.