REAL-TIME DEPTH MAP ESTIMATION FROM INFRARED STEREO IMAGES OF RGB-D CAMERAS

Abstract. RGB-D cameras are novel sensing systems that can rapidly provide accurate depth information for 3D perception, among which the type based on active stereo vision has been widely used. However, there are some problems exiting in use, such as the short measurement range and incomplete depth maps. This paper presents a robust and efficient matching algorithm based on semi-global matching to obtain more complete and accurate depth maps in real time. Considering characteristics of captured infrared speckle images, the Gaussian filter is performed firstly to restrain noise and enhance the relativity. It also adopts the idea of block matching for reliability, and a dynamic threshold selection of the block size is used to adapt to various situation. Moreover, several optimizations are applied to improve precision and reduce error. Through experiments on the Intel Realsense R200, the excellent capability of our proposed method is verified.