3DUNDERWORLD-SLS vs MeshLab

3DUNDERWORLD-SLS is a free Linux project that reconstructs point clouds from camera image sequences illuminated by patterned light. Its structured-light process has CPU and GPU implementations, and the command-line program can save reconstructed models as PLY or OBJ files. Version 4.x requires two or more cameras and provides a generic camera interface that programmers can extend. Camera acquisition is not implemented, so users must supply a camera class through the provided interfaces. The project accepts camera image folders, calibration files, and a patterned-light projector as inputs. It does not provide real-time capture or mesh reconstruction. Libraries are included for integration into other projects, with CPU and GPU examples, and an API was included in OpenCV 3.1 for a stereo approach using time-multiplexing Gray encoding. The repository supplies demo binaries, example data, and CMake build instructions. Dependencies are OpenCV 2, CUDA 6.0 or later, and glm. CUDA detection enables CPU and GPU constructors; without CUDA, only the CPU constructor is generated.

MeshLab is a free desktop system for processing and editing 3D triangular meshes, including unstructured models produced by 3D scanning. Its tools cover editing, cleaning, repair, inspection, rendering, texturing, and conversion. The site describes using it to process raw data from 3D digitization and prepare models for 3D printing. MeshLab supports PTX point-cloud and range-map files, and listed export formats include PLY, STL, OBJ, OFF, WRL, and DXF. It runs on Windows, macOS, and Linux and is distributed under the GPL 3.0 license. PyMeshLab provides a Python interface for loading and saving meshes and applying MeshLab filters; the VCG code can be used in a standalone, large-scale automated processing pipeline. The listed MeshLab 2025.07 release is dated September 9, 2025, and includes ARM64 support on Linux and macOS plus 3MF support. The site points usage questions to Stack Overflow and bug reports to GitHub, with video learning resources for basics, features, scanning workflows, and mesh cleaning.