Robustness of ToF and Stereo Fusion for High Accuracy Depth Maps

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 main technical means to obtain depth information, but each of two systems alone has its own limitations. In this paper, Time-of-Flight (ToF) and stereo fusion framework is proposed to solve 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 stereo matching of passive stereo in the prior fusion stage. During the post fusion stage, weighting function is designed according to depth map of stereo matching and credibility map of ToF depth map, and then 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 other fusion approaches.