Robustness of ToF and stereo fusion for high-accuracy depth map

Abstract

Depth map can be used in many applications such as robotic navigation, driverless, video production and 3D reconstruction. Currently, both active depth cameras and passive stereo vision systems are the main technical means to obtain depth information, but each of the two systems alone has its own limitations. In this paper, the Time-of-Flight (ToF) and stereo fusion framework is proposed to solve the limitations of these two systems. The scheme in this paper contains "the prior fusion stage" and "the post fusion stage". Using depth information design energy function from ToF cameras to boost the stereo matching of passive stereo in "the prior fusion stage". During "the post fusion stage", the weighting function is designed according to the depth map of the stereo matching and the credibility map of the ToF depth map, and then the adaptive weighted depth fusion is performed. Experimental results clearly show that our method can obtain high-precision and high-resolution depth maps with better robustness than the other fusion approaches.