Depth extraction for a structured light system based on mismatched image pair rectification using a virtual camera

Structured light systems have become an effective tool for reconstructing three-dimensional models of objects due to the advent of low-price, high-speed depth cameras such as Kinect. However, this kind of active depth sensor extracts low-quality depth maps because of its inaccurate image matching process. This study proposes a depth extraction method based on image rectification for accurate image matching. Due to the sizes of the projected patterns and the captured images are usually different, a virtual camera is defined, through which the rectified images are generated to match the images in the real camera at pixel level. Experiments on simulated and hardware platforms demonstrate that the proposed method achieves efficient rectification and obtains better-quality depth maps.