ML Anthology

Correspondence-Free Material Reconstruction Using Sparse Surface Constraints

Sebastian Weiss, Robert Maier, Daniel Cremers, Rudiger Westermann, Nils Thuerey
CVPR 2020
doi:10.1109/CVPR42600.2020.00474 /cvpr/2020/weiss2020cvpr-correspondencefree/

Abstract

We present a method to infer physical material parameters, and even external boundaries, from the scanned motion of a homogeneous deformable object via the solution of an inverse problem. Parameters are estimated from real-world data sources such as sparse observations from a Kinect sensor without correspondences. We introduce a novel Lagrangian-Eulerian optimization formulation, including a cost function that penalizes differences to observations during an optimization run. This formulation matches correspondence-free, sparse observations from a single-view depth image with a finite element simulation of deformable bodies. In a number of tests using synthetic datasets and real-world measurements, we analyse the robustness of our approach and the convergence behavior of the numerical optimization scheme.

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Cite

Text

Weiss et al. "Correspondence-Free Material Reconstruction Using Sparse Surface Constraints." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.00474

Markdown

[Weiss et al. "Correspondence-Free Material Reconstruction Using Sparse Surface Constraints." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/weiss2020cvpr-correspondencefree/) doi:10.1109/CVPR42600.2020.00474

BibTeX

@inproceedings{weiss2020cvpr-correspondencefree,
  title     = {{Correspondence-Free Material Reconstruction Using Sparse Surface Constraints}},
  author    = {Weiss, Sebastian and Maier, Robert and Cremers, Daniel and Westermann, Rudiger and Thuerey, Nils},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2020},
  doi       = {10.1109/CVPR42600.2020.00474},
  url       = {https://mlanthology.org/cvpr/2020/weiss2020cvpr-correspondencefree/}
}