MATLAB Code Implementation for 3D Point Cloud Reconstruction

This MATLAB-based point cloud 3D reconstruction code program represents a computer vision methodology that processes Kinect depth images, converts them into point cloud data, and reconstructs realistic 3D models through sophisticated algorithms. The implementation employs key MATLAB functions including depth image preprocessing routines (noise removal using medfilt2, smoothing with imgaussfilt), point cloud conversion using depth2cloud coordinate transformation, and reconstruction algorithms such as Poisson surface reconstruction or moving least squares (MLS) smoothing. The technical workflow involves critical processing stages: depth image preprocessing for noise reduction and smoothing, point cloud data conversion through depth-to-3D coordinate mapping, point cloud registration using ICP (Iterative Closest Point) algorithm for multi-view alignment, and final 3D reconstruction with surface generation techniques. This technology finds extensive applications in 3D modeling, virtual reality systems, and robotic vision, where the code specifically handles depth image calibration, point cloud downsampling using pcdownsample, and mesh generation via pcsurface functions to produce high-quality 3D models suitable for professional applications.