  This article describes a technique to augment a typical RGBD sensor by
integrating depth estimates obtained via Structure-from-Motion (SfM) with
sensor depth measurements. Limitations in the RGBD depth sensing technology
prevent capturing depth measurements in four important contexts: (1) distant
surfaces (>5m), (2) dark surfaces, (3) brightly lit indoor scenes and (4)
sunlit outdoor scenes. SfM technology computes depth via multi-view
reconstruction from the RGB image sequence alone. As such, SfM depth estimates
do not suffer the same limitations and may be computed in all four of the
previously listed circumstances. This work describes a novel fusion of RGBD
depth data and SfM-estimated depths to generate an improved depth stream that
may be processed by one of many important downstream applications such as
robotic localization and mapping, as well as object recognition and tracking.
