MVE vs OpenMVG
MVE
github.comOpenMVG
github.comSide by side
| Figure | MVE | OpenMVG |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · Photogrammetry Software | 7.2 (#26) | 8.6 (#4) |
| License | The wiki says source files are distributed under the BSD 3-Clause License unless a source file states otherwise. | The repository identifies the project license as Mozilla Public License 2.0. |
| Platforms | The wiki says MVE runs on Linux, MacOS X, and Windows. | The project says it runs on Android, iOS, Linux, macOS, and Windows. |
| Purpose | MVE is an end-to-end pipeline for image-based geometry reconstruction, including Structure-from-Motion, Multi-View Stereo, and surface reconstruction. | OpenMVG is a multiple view geometry library for 3D computer vision and structure from motion. |
Plans
In their own words
OpenMVG
OpenMVG is an open-source C++ library for multiple-view geometry, 3D computer vision, and structure from motion. It provides libraries, binaries, and pipelines for reconstructing 3D scenes from images. Library areas include image manipulation, feature description and matching, feature tracking, camera models, multiple-view geometry, robust estimation, and structure-from-motion algorithms. Its binaries can initialize scenes, detect and match features, perform reconstruction, and export scenes to other multiple-view-stereo frameworks. Those frameworks can compute dense point clouds or textured meshes from exported scenes. OpenMVG is released under the Mozilla Public License 2.0 and is listed as free. The project says it aims to support reproducible research through readable implementations of classic and state-of-the-art algorithms. It is designed for reading, learning, modification, and use, with test-driven development and samples. Tutorials cover data structures, library use, and processing an image dataset. Platforms listed are Windows, macOS, Linux, iOS, Android, and self-hosted, with desktop deployment, API access, point-cloud export, and ground control point support.