K-nearest neighborhood based integration of time-of-flight cameras and passive stereo for high-accuracy depth maps

Both time-of-flight (ToF) cameras and passive stereo can provide the depth information for their corresponding captured real scenes, but they have innate limitations. ToF cameras and passive stereo are intrinsically complementary for certain tasks. It is desirable to appropriately leverage all the available information by ToF cameras and passive stereo. Although some fusion methods have been presented recently, they fail to consider ToF reliability detection and ToF based improvement of passive stereo. As a result, this study proposes an approach to integrating ToF cameras and passive stereo to obtain high-accuracy depth maps. The main contributions are: (1) An energy cost function is devised to use data from ToF cameras to boost the stereo matching of passive stereo; (2) A fusion method is used to combine the depth information from both ToF cameras and passive stereo to obtain high-accuracy depth maps. Experiments show that the proposed approach achieves improved results with high accuracy and robustness.