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On the recordRead 8 Oct 202624 facts

3DUNDERWORLD-SLS

Montreal, Quebec

Visit github.com Alternatives

What it is

3DUNDERWORLD-SLS is free Linux software that reconstructs point clouds from camera image sequences illuminated by patterned light. It provides CPU and GPU implementations and command-line output in PLY or OBJ format. Version 4.x expects two or more cameras and offers a generic camera interface that programmers can extend, but camera acquisition is not implemented; users must provide a camera class. The project includes integration libraries, CPU and GPU examples, and an API included in OpenCV 3.1 for a stereo approach using time-multiplexing Gray encoding. Demo binaries, sample data, and CMake build instructions are included. Dependencies are OpenCV 2, CUDA 6.0 or later, and glm. CUDA detection creates CPU and GPU constructors; without CUDA, the default build creates only the CPU constructor. The repository uses the GNU Lesser General Public License version 3 with additional permissions. It does not provide real-time capture or mesh reconstruction. Users of resulting publications are asked to cite specified publications.

For and against

For

  • CPU and GPU reconstruction paths
  • PLY and OBJ export
  • Extensible camera interface
  • Libraries and integration API
  • CMake build instructions included

Against

  • Camera acquisition must be implemented
  • Requires two or more cameras
  • Depends on older OpenCV 2
  • No real-time capture or mesh reconstruction

The verdict

3DUNDERWORLD-SLS provides a research-oriented structured-light point-cloud pipeline with extensible interfaces and CPU/GPU options. Its missing camera acquisition and build dependencies mean it requires technical setup rather than plug-and-play scanning.

Who it suits

This project suits developers and researchers building structured-light scanning workflows on Linux. It is intended for users able to implement camera acquisition and compile software with its listed dependencies.

On the record

Build
The repository includes demo binaries and data, and a CMake script to compile the binaries and libraries.github.com · read 7 Oct 2026
Build requirements
The listed dependencies are OpenCV 2, CUDA 6.0 or later, and glm.github.com · read 8 Oct 2026
Camera acquisition
Camera acquisition is not implemented, though the project provides interfaces for users to implement a camera class.github.com · read 7 Oct 2026
Camera limitation
Camera acquisition is not implemented; the project provides interfaces for users to implement a camera class.github.com · read 8 Oct 2026
CPU and GPU
The reconstruction process is implemented for both CPU and GPU, with CUDA-enabled builds generating both CPU and GPU executables when CUDA is detected.github.com · read 8 Oct 2026
Data size
The repository notes that its included example data makes the repository about 300 MB.github.com · read 7 Oct 2026
Dependencies
The listed dependencies are OpenCV 2, CUDA 6.0 or later, and glm.github.com · read 7 Oct 2026
Download and build
The repository includes demo binaries and data and provides CMake instructions to build the binaries and libraries.github.com · read 8 Oct 2026
GPU support
If CUDA is detected, the default build creates CPU and GPU constructors; otherwise, it generates only the CPU constructor.github.com · read 7 Oct 2026
Integration
The project provides libraries intended for integration into other projects, with CPU and GPU application examples in the repository.github.com · read 8 Oct 2026
Intended use
The project's technical report describes the system as an open-source structured-light scanner for rapid geometry acquisition.theictlab.org · read 7 Oct 2026
Intended users
The lab describes its work as research and notes collaborations with industry and other external partners.theictlab.org · read 8 Oct 2026
Library
The project includes libraries intended for integration into other projects, with CPU and GPU application examples.github.com · read 7 Oct 2026
License
The GitHub repository identifies its license as LGPL-3.0.github.com · read 8 Oct 2026
Output
The command-line program can export reconstructed models in PLY or OBJ format.github.com · read 7 Oct 2026
Outputs
The demo accepts camera image folders and calibration files and can save output as PLY or OBJ.github.com · read 8 Oct 2026
Processing
Image processors use images, projector parameters, and camera calibration parameters to produce data that the reconstructor combines into a point cloud.github.com · read 8 Oct 2026
Project status
The lab's software page lists GPU-based structured-light scanning software V4.0 under “Under Active Development.”theictlab.org · read 8 Oct 2026

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