A single-camera system captures high-resolution 3D images in one shot
暂无分享,去创建一个
Although we live in a 3D world, most of the data we record and display is still in 1D or 2D formats. As a result, data from the third dimension, which is often important in aiding human judgments, cannot be stored. In many cases, the depth information that is lost when data is stored in 1D or 2D formats is critical for measuring an object’s surface shape and profile, as well as perceiving its distance. To address these issues, researchers have been investigating methods of acquiring 3D information from objects and scenes for many years. There are several existing techniques for 3D measurements, including laser scanning techniques, and grating projection, stereo vision, and time-of-flight methods. We introduce a prism/mirror optical setup to combine two stereo-view pairs into one image using a single digital camera. This 3D imaging technology combines structured light projection and stereo vision techniques in a unique way: it splits a single camera view into stereo vision, with an option to project a color-coded structure light onto the object using a synchronized flash light source, as shown in Figure 1. 3 It achieves 3D imaging in a single flash of less than 1/100 of a second, and is therefore robust to object motion and changing environments. It is accurate down to 0.1mm in depth resolution. We have also developed advanced algorithms for generating 3D models fast and accurately. Before it is used to capture data, the 3D camera is first calibrated. The calibration procedure calculates three external parameters: the rotation matrix R, the translation vector t, and the camera internal calibration matrix K. The parameters are further optimized by applying a bundle adjustment algorithm, which can be used to determine the optimal position of the camera and 3D data points during the capture process. Figure 1. A single digital camera-based 3D imaging system consists of an optical mirror and prism setup, creating the equivalent of stereo vision from two virtual cameras.
[1] Rachid Deriche,et al. A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry , 1995, Artif. Intell..
[2] Tien-Hsin Chao,et al. A high resolution and high speed 3D imaging system and its application on ATR , 2006, SPIE Defense + Commercial Sensing.
[3] O. Faugeras. Three-dimensional computer vision: a geometric viewpoint , 1993 .
[4] Aaron Fenster,et al. Three-dimensional imaging system , 2003 .