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

作　　者：Li-wei LIU Yang LI Ming ZHANG Liang-hao WANG Dong-xiao LI 

机构地区：[1]Institute of Information and Communication Engineering, Zhejiang University [2]Zhejiang Provincial Key Laboratory of Information Network Technology

出　　处：《Journal of Zhejiang University-Science C(Computers and Electronics)》2014年第3期174-186,共13页浙江大学学报C辑（计算机与电子（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Nos.61072081 and 61271338);the National High-Tech R&D Program(863)of China(No.2012AA011505);the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2009ZX01033-001-007);the Key Science and Technology Innovation Team of Zhejiang Province(No.2009R50003);the China Postdoctoral Science Foundation(No.2012T50545)

摘　　要：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.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.

关 键 词：Depth map Passive stereo Time-of-flight camera Fusion 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]