基于场景模型的双目相机动态检校方法

提出了一种基于场景模型的双目相机内、外方位元素的动态检校方法.初始检校过程构建了场景全局三维模型并以此为基础分别初步解算内、外方位元素，然后进行联合优化；更新检校过程利用已建立的场景模型，恢复场景模型与影像的关联，再通过联合优化更新相机的检校参数.实际场景实验验证结果表明：该方法的检校完整度优于基于即时定位和地图构建(SLAM)的检校方法，精度优于传统棋盘格检校方法.
A scene model based stereo-camera calibration method is presented in this paper. The initial calibration process firstly constructs a global scene model, and based on this, both intrinsic and extrinsic parameters of the stereo camera are estimated separately and optimized jointly. The update calibration utilizes the established scene model to restore three dimention two dimention relation between model coordinate and image coordinate, with the relation, stereo camera parameters are updated through joint optimization. The experiments in real world show that the method calibrates all the parameters while SLAM based method only solves a part, and the accuracy of the method is better than the chess board based method