Symmetry-driven 3D Reconstruction from Concept Sketches
Concept sketches, ubiquitously used in industrial design, are inherently imprecise yet highly effective at communicating 3D shape to human observers. We present a new symmetry-driven algorithm for recovering designer-intended 3D geometry from concept sketches. We observe that most concept sketches of human-made shapes are structured around locally symmetric building blocks, defined by triplets of orthogonal symmetry planes. We identify potential building blocks using a combination of 2D symmetries and drawing order. We reconstruct each such building block by leveraging a combination of perceptual cues and observations about designer drawing choices. We cast this reconstruction as an integer programming problem where we seek to identify, among the large set of candidate symmetry correspondences formed by approximate pen strokes, the subset that results in the most symmetric and well-connected shape. We demonstrate the robustness of our approach by reconstructing 82 sketches, which exhibit significant over-sketching, inaccurate perspective, partial symmetry, and other imperfections. In a comparative study, participants judged our results as superior to the state-of-the-art by a ratio of 2:1.
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Acknowledgements
This work was supported by the ERC Starting Grant D3 (ERC- 2016-STG 714221), the Natural Sciences and Engineering Research Council of Canada (NSERC) grant RGPIN-2018-03944, and research and software donations from Adobe.
BibTex references
@InProceedings{HGSB22, author = "H{\"a}hnlein, Felix and Gryaditskaya, Yulia and Sheffer, Alla and Bousseau, Adrien", title = "Symmetry-driven 3D Reconstruction from Concept Sketches", booktitle = "SIGGRAPH", year = "2022", publisher = "ACM", url = "http://www-sop.inria.fr/reves/Basilic/2022/HGSB22" }