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TurboSL: Dense Accurate and Fast 3D by Neural Inverse Structured Light

Parsa Mirdehghan · Maxx Wu · Wenzheng Chen · David B. Lindell · Kiriakos Kutulakos

Arch 4A-E Poster #83
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Fri 21 Jun 5 p.m. PDT — 6:30 p.m. PDT


We show how to turn a noisy and fragile active triangulation technique—three-pattern structured light with a grayscale camera—into a fast and powerful tool for 3D capture: able to output sub-pixel accurate disparities at megapixel resolution, along with reflectance, normals, and a no-reference estimate of its own pixelwise 3D error. To achieve this, we formulate structured-light decoding as a neural inverse rendering problem. We show that despite having just three or four input images—all from the same viewpoint—this problem can be tractably solved by TurboSL, an algorithm that combines (1) a precise image formation model, (2) a signed distance field scene representation, and (3) projection pattern sequences optimized for accuracy instead of precision. We use TurboSL to reconstruct a variety of complex scenes from images captured at up to 60 fps with a camera and a common projector. Our experiments highlight TurboSL’s potential for dense and highly-accurate 3D acquisition from data captured in fractions of a second.

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