3D Reconstruction and 3D Scene Modeling
3D reconstruction, 3D scene modeling with stereo vision MATLAB source code implementation
Key Technology in Stereo Vision: Solving the Correspondence Problem
The core challenge in stereo vision involves resolving correspondence issues, where point features serve as primary descriptors. The influential HARRIS corner detection operator, implemented here using MATLAB, provides robust feature identification for image processing workflows.
Fundamental Matrix Computation for Stereo Vision Cameras
This algorithm implements fundamental matrix computation for stereo vision cameras in MATLAB 2008b environment. It includes four main functions: main, sevenPoint, eightpoint, and eightpoint_norm. The main.m serves as the program entry point, handling experimental data generation and loading, calling the three fundamental matrix computation functions, and visualizing the results. The sevenPoint.m implements the 7-point algorithm, eightpoint.m uses the standard 8-point algorithm, while eightpoint_norm.m performs data normalization before applying the 8-point method for improved numerical stability.
Camera Calibration in Stereo Vision
Camera calibration program for stereo vision using the Zhang's calibration method! A highly practical implementation featuring robust parameter estimation and automated error correction.
Active Vision Camera Calibration
Active vision camera calibration program based on Ma Songde's stereo vision calibration method, featuring robust implementation with corner detection and pose estimation algorithms. Contact me for testing code and detailed documentation!
3D Reconstruction
3D Reconstruction Techniques and MATLAB Implementation