Explore MATLAB source code curated for "三维重建" with clean implementations, documentation, and examples.
This project provides a MATLAB implementation of the graph cut algorithm featuring parameter estimation capabilities applicable to 3D reconstruction. The code demonstrates energy minimization using max-flow/min-cut optimization with adjacency matrix construction.
MATLAB-based 3D reconstruction implementation featuring stereo image matching point extraction algorithms
Perform 3D reconstruction from multiple images by obtaining camera intrinsic parameters through calibration toolbox, followed by texture mapping for realistic visualization.
A voxel-based 3D reconstruction program from 2D photos, incorporating pre-reconstruction error analysis to achieve satisfactory reconstruction results. The implementation includes algorithms for edge detection and shape recognition through pixel density and color analysis.
This MATLAB-based implementation utilizes pseudo-random principles to generate color-encoded patterns with window characteristics, specifically designed for 3D reconstruction research. The code demonstrates pattern generation algorithms and includes configurable parameters for window size optimization. Technical guidance available via QQ: 526289.
Implementing 3D brain visualization by reading CT image datasets, providing practical learning experience for MATLAB-based CT image three-dimensional reconstruction processes with code implementation details.
This algorithm calculates the center position of cross-shaped markers with sub-pixel accuracy, commonly used in 3D reconstruction where markers are placed on object surfaces. The implementation typically involves image processing techniques, pattern recognition, and centroid calculation methods.
MATLAB source code for fundamental 3D matching algorithms, featuring image processing techniques and 3D reconstruction capabilities with practical implementation examples
Stereo Vision 3D Reconstruction Program - Inputs matching point pair matrices from left/right cameras, automatically computes projection matrices, and outputs 3D point coordinates in projective space using triangulation algorithms.
Disparity map generation for stereo image pairs enables subsequent 3D reconstruction applications through pixel-wise correspondence matching.