Computing depth under ambient illumination using multi-shuttered light

Range imaging has become a critical component of many computer vision applications. The quality of the depth data is of critical importance, but so is the need for speed. Shuttered light-pulse (SLP) imaging uses active illumination hardware to provide high quality depth maps at video frame rates. Unfortunately, current analytical models for deriving depth from SLP imagers are specific to the number of shutters and have a number of deficiencies. As a result, depth estimation often suffers from bias due to object reflectivity, incorrect shutter settings, or strong ambient illumination such as that encountered outdoors. These limitations make SLP imaging unsuitable for many applications requiring stable depth readings. This paper introduces a method that is general to any number of shutters. Using three shutters, the new method produces invariant estimates under changes in ambient illumination, producing high quality depth maps in a wider range of situations.