  Passive depth estimation is among the most long-studied fields in computer
vision. The most common methods for passive depth estimation are either a
stereo or a monocular system. Using the former requires an accurate calibration
process, and has a limited effective range. The latter, which does not require
extrinsic calibration but generally achieves inferior depth accuracy, can be
tuned to achieve better results in part of the depth range. In this work, we
suggest combining the two frameworks. We propose a two-camera system, in which
the cameras are used jointly to extract a stereo depth and individually to
provide a monocular depth from each camera. The combination of these depth maps
leads to more accurate depth estimation. Moreover, enforcing consistency
between the extracted maps leads to a novel online self-calibration strategy.
We present a prototype camera that demonstrates the benefits of the proposed
combination, for both self-calibration and depth reconstruction in real-world
scenes.
