Surface Reconstruction from Structured Light Images Using Differentiable Rendering
Autor: | Jakob Wilm, Anders Bjorholm Dahl, Morten Hannemose, Janus Nørtoft Jensen, J. Andreas Bærentzen, Jeppe Revall Frisvad |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
structured light
Vertex (computer graphics) Computer science Point cloud ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Initialization 02 engineering and technology lcsh:Chemical technology Biochemistry Article Analytical Chemistry Rendering (computer graphics) Structured-light 3D scanner Triangle mesh 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 3D scanning Electrical and Electronic Engineering Instrumentation differentiable rendering ComputingMethodologies_COMPUTERGRAPHICS 3D surface reconstruction Structured light 020207 software engineering Atomic and Molecular Physics and Optics Vertex (geometry) Differentiable rendering 020201 artificial intelligence & image processing Algorithm Surface reconstruction |
Zdroj: | Sensors Volume 21 Issue 4 Jensen, J N, Hannemose, M, Bærentzen, J A, Wilm, J, Frisvad, J R & Dahl, A B 2021, ' Surface reconstruction from structured light images using differentiable rendering ', Sensors (Switzerland), vol. 21, no. 4, 1068, pp. 1-16 . https://doi.org/10.3390/s21041068 Sensors, Vol 21, Iss 1068, p 1068 (2021) Jensen, J N, Hannemose, M, Bærentzen, J A, Wilm, J, Frisvad, J R & Dahl, A B 2021, ' Surface reconstruction from structured light images using differentiable rendering ', Sensors (Switzerland), vol. 21, no. 4, 1068 . https://doi.org/10.3390/s21041068 Sensors (Basel, Switzerland) |
ISSN: | 1424-8220 |
DOI: | 10.3390/s21041068 |
Popis: | When 3D scanning objects, the objective is usually to obtain a continuous surface. However, most surface scanning methods, such as structured light scanning, yield a point cloud. Obtaining a continuous surface from a point cloud requires a subsequent surface reconstruction step, which is directly affected by any error from the computation of the point cloud. In this work, we propose a one-step approach in which we compute the surface directly from structured light images. Our method minimizes the least-squares error between photographs and renderings of a triangle mesh, where the vertex positions of the mesh are the parameters of the minimization problem. To ensure fast iterations during optimization, we use differentiable rendering, which computes images and gradients in a single pass. We present simulation experiments demonstrating that our method for computing a triangle mesh has several advantages over approaches that rely on an intermediate point cloud. Our method can produce accurate reconstructions when initializing the optimization from a sphere. We also show that our method is good at reconstructing sharp edges and that it is robust with respect to image noise. In addition, our method can improve the output from other reconstruction algorithms if we use these for initialization. |
Databáze: | OpenAIRE |
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