MetaScan vs OpenMVG

MetaScan creates 3D models of people and objects through a mobile app or an event scanning service. Its app offers object, full-body and head-and-shoulders capture using photogrammetry on modern iPhone or Android cameras, without requiring LiDAR. Scans can be viewed in augmented reality and exported as GLB, USDZ or OBJ; MetaScan also says they can be auto-rigged and animated for use in its multiplayer game In The Real World. Browser-based converters support GLB, OBJ, STL, glTF, PLY, FBX and USDZ, processing files on the user's device without uploading them. Event services include a scanning station, portrait studio and 360 spin video booth for occasions such as weddings, team days and corporate events. The free plan allows up to five scans in a library and one HD reconstruction per month. Pro costs $9.99 a month, Studio costs $29.99 a month, and an HD credit costs 4.99 USD once. MetaScan says person scans require consent and source images for standard scans are deleted automatically about two hours after model generation. It offers support by phone, text, email or website message.

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.