MATLAB Code Implementation for 3D Point Cloud Reconstruction
MATLAB-based point cloud 3D reconstruction code program demonstrating the complete pipeline from Kinect depth image processing to point cloud conversion and final 3D model reconstruction.
3D Reconstruction from Point Clouds
Implementation of 3D reconstruction from point cloud data using MATLAB, featuring multiple examples and various point cloud images with excellent reconstruction results. The implementation covers point cloud processing, surface reconstruction algorithms, and visualization techniques.
3D Point Cloud Reconstruction
Point cloud 3D reconstruction algorithm implemented in MATLAB, delivering excellent results with efficient processing speed suitable for large-scale data applications
Point Cloud Triangular Reconstruction Using MATLAB
Point Cloud Triangular Reconstruction Implementation with MATLAB
Finding k-Nearest Neighbors in 3D Laser Scanning Point Clouds Using Spatial Bounding Box Method
Locating k-nearest neighbors for each point in 3D laser scanning point clouds through spatial bounding box partitioning approach with code implementation insights
3D Mesh Reconstruction from Point Clouds
Implementation of 3D mesh reconstruction from point clouds with included test point cloud datasets for validation
3D Reconstruction MATLAB Program Based on Two-View Geometry
Complete and tested MATLAB program for 3D reconstruction from two views, implementing point cloud generation, feature matching, and full reconstruction pipeline. This program reconstructs 3D scenes using two images taken from different viewpoints, demonstrating practical implementation of stereo vision algorithms.
Point Cloud Registration Experiment: Implementing Alignment of Two Point Cloud Datasets Using S-ICP Algorithm
Experimental point cloud registration using the S-ICP algorithm to achieve alignment between two point cloud datasets with code implementation insights
Implementation of ICP Registration Algorithm
Developed an ICP registration algorithm using VC++, compiled into a dynamic-link library. The CallICP function enables precise registration between two point clouds with robust error minimization.
Point Clouds from 3D Laser Scanning: Local Neighborhood Plane Fitting
Processing 3D laser scanning point clouds by fitting planes within local neighborhoods - a fundamental technique for planar surface extraction with implementation insights using PCA and RANSAC algorithms.