  It is well known that the passive stereo system cannot adapt well to weak
texture objects, e.g., white walls. However, these weak texture targets are
very common in indoor environments. In this paper, we present a novel stereo
system, which consists of two cameras (an RGB camera and an IR camera) and an
IR speckle projector. The RGB camera is used both for depth estimation and
texture acquisition. The IR camera and the speckle projector can form a
monocular structured-light (MSL) subsystem, while the two cameras can form a
binocular stereo subsystem. The depth map generated by the MSL subsystem can
provide external guidance for the stereo matching networks, which can improve
the matching accuracy significantly. In order to verify the effectiveness of
the proposed system, we build a prototype and collect a test dataset in indoor
scenes. The evaluation results show that the Bad 2.0 error of the proposed
system is 28.2% of the passive stereo system when the network RAFT is used. The
dataset and trained models are available at
https://github.com/YuhuaXu/MonoStereoFusion.
