MATLAB Dual-Camera Calibration Example Based on Binocular Stereo Vision Imaging Principles

This article presents a MATLAB-based dual-camera calibration example grounded in binocular stereo vision imaging principles. The example package includes calibration images, fully functional programs, and comprehensive documentation designed to help readers understand and apply binocular stereo vision technology effectively. Binocular stereo vision mimics human binocular perception by using two cameras to capture images from different viewpoints - through disparity calculation between corresponding points in stereo image pairs, the system achieves depth perception and 3D reconstruction capabilities. This implementation demonstrates camera calibration using MATLAB's Computer Vision Toolbox, specifically utilizing the stereoCameraCalibrator app and related functions for detecting checkerboard patterns, estimating intrinsic/extrinsic parameters, and calculating stereo rectification transforms. The code example includes key functions like detectCheckerboardPoints for corner detection, estimateCameraParameters for calibration computation, and stereoParameters for storing calibration results. Through this practical example, readers will master fundamental binocular vision concepts while learning to implement camera calibration workflows that can be directly applied to real-world projects involving depth estimation and 3D scene reconstruction. Should you have any technical questions regarding the implementation or theoretical aspects, please feel free to ask for clarification.