3D Reconstruction Using Binocular Vision with MATLAB Implementation

Three-dimensional reconstruction based on binocular vision is a modeling technique that simulates human binocular vision systems through computational methods. This technology utilizes two cameras to capture different images of the same scene, then combines these images using computer algorithms to generate stereoscopic representations. Key implementation steps in MATLAB typically involve camera calibration using the Camera Calibration Toolbox, stereo image rectification with epipolar geometry, disparity map calculation through block matching or semi-global matching algorithms, and depth estimation via triangulation methods. The technology finds extensive applications across various fields including medical imaging, robotics navigation, and gaming industries. MATLAB's implementation offers significant advantages through its comprehensive Image Processing Toolbox and Computer Vision Toolbox, which provide built-in functions for stereo calibration (stereoParameters), disparity estimation (disparitySGM), and point cloud generation (reconstructScene). This facilitates efficient image processing and analysis, thereby substantially improving reconstruction accuracy and computational efficiency. Consequently, 3D reconstruction technology based on binocular vision and its MATLAB implementation hold considerable research significance and practical application value in computer vision domains.