SLAM-Based Self-Calibration of a Binocular Stereo Vision Rig in Real-Time

The calibration problem of binocular stereo vision rig is critical for its practical application. However, most existing calibration methods are based on manual off-line algorithms for specific reference targets or patterns. In this paper, we propose a novel simultaneous localization and mapping (SLAM)-based self-calibration method designed to achieve real-time, automatic and accurate calibration of the binocular stereo vision (BSV) rig’s extrinsic parameters in a short period without auxiliary equipment and special calibration markers, assuming the intrinsic parameters of the left and right cameras are known in advance. The main contribution of this paper is to use the SLAM algorithm as our main tool for the calibration method. The method mainly consists of two parts: SLAM-based construction of 3D scene point map and extrinsic parameter calibration. In the first part, the SLAM mainly constructs a 3D feature point map of the natural environment, which is used as a calibration area map. To improve the efficiency of calibration, a lightweight, real-time visual SLAM is built. In the second part, extrinsic parameters are calibrated through the 3D scene point map created by the SLAM. Ultimately, field experiments are performed to evaluate the feasibility, repeatability, and efficiency of our self-calibration method. The experimental data shows that the average absolute error of the Euler angles and translation vectors obtained by our method relative to the reference values obtained by Zhang’s calibration method does not exceed 0.5˚ and 2 mm, respectively. The distribution range of the most widely spread parameter in Euler angles is less than 0.2˚ while that in translation vectors does not exceed 2.15 mm. Under the general texture scene and the normal driving speed of the mobile robot, the calibration time can be generally maintained within 10 s. The above results prove that our proposed method is reliable and has practical value.

Miniaturized three-dimensional endoscopic imaging system based on active stereovision

A miniaturized three-dimensional endoscopic imaging system is presented. The system consists of two imaging in channels that can be used to obtain an image from an object of interest and to project as tructured light onto the imaged object to measure the surface topology. The structured light was generated with a collimated monochromatic light source and a holographic binary phase grating. The imaging and projection channels were calibrated by use of a modified pinhole camera. The surface profile was extracted by use of triangulation between the projected feature points and the two channel ofthe endoscope. The imaging system was evaluated in three-dimensional measurements of several objects with known geometries. The results show that surface profiles of the objects with different surfaces and dimensions can be obtained at high accuracy. The in vivo measurements at tissue sites of human skin and an oral cavity demonstrated the potential of the technique for clinical applications.