3D Reconstruction from Multiple Images Using Camera Calibration Toolbox and Texture Mapping

Prior to conducting 3D reconstruction, it is essential to utilize a camera calibration toolbox (such as MATLAB's Camera Calibrator or OpenCV's calibration module) to extract critical camera parameters including intrinsic matrix, distortion coefficients, and focal length. The calibration process typically involves capturing multiple images of a calibration pattern (like a chessboard) from different angles and using optimization algorithms to minimize reprojection errors. Following calibration, multi-view 3D reconstruction can be performed through structure-from-motion (SfM) pipelines, where feature detection algorithms (e.g., SIFT or ORB) identify keypoints across images, followed by bundle adjustment to optimize 3D point positions and camera poses. Finally, texture mapping is applied using UV unwrapping techniques, where surface textures are projected from original images onto the reconstructed mesh using coordinate mapping functions, enhancing visual realism through proper illumination modeling and seam blending algorithms.