A recent project shared on reddit - r/esp32 showcases how much computer vision potential can be squeezed out of inexpensive, low-power hardware. Built around a Seeed Studio XIAO ESP32-S3 board paired with its dedicated round screen extension, the handheld device doubles as a self-contained 3D object scanner. Originally intended as a platform for an augmented reality game, the creator pivoted to 3D reconstruction by leveraging pose estimation software along with classic computer vision algorithms, all executing directly on a setup costing roughly $20.
Under the hood, the handheld scanner uses a combination of space carving and marching cubes to turn real-world objects into digital 3D meshes. The system calculates camera positioning relative to the subject using fiducial markers on a tracking target. As the device moves around an object, the space carving algorithm aggregates multiple camera views to build a voxel grid, weighting voxels based on sightline agreement across frames. A Look-Up Table (LUT) implementation of the marching cubes algorithm then converts those voxels into a exportable triangle mesh. The developer overcame significant memory and pipeline hurdles, such as switching dynamically between a live 240x240 preview feed for the round display and high-resolution image captures for processing.
While modern smartphones offer far more polished photogrammetry apps, this DIY project demonstrates the remarkable capability of microcontroller-class hardware. The scanner currently achieves roughly 1 mm structural resolution, making it suitable for capturing small trinkets or field specimens like rocks and leaves. It stands as an impressive proof of concept for budget embedded vision, opening doors for field-ready digital twin capture and accessible 3D modeling tools for the maker community.
Add a comment
No account needed. Your comment appears once a moderator has reviewed it.