Fast and Globally Optimal Single View Reconstruction of Curved Objects
Abstract
We propose a novel algorithmic solution for estimating a three-dimensional model of an object observed in a single image. Based on a minimal user input, the algorithm interactively determines the objects' silhouette and subsequently computes a silhouette-consistent 3D model which is precisely the globally minimal surface with user-specified volume. In contrast to a recently published approach to single view reconstruction, the proposed algorithm does not constrain the resolution in the depth-direction, it assures the global optimum and is faster by about an order of magnitude. Experiments demonstrate that plausible high-resolution 3D models can be generated in fractions of a second and compare favorably with other methods.
Cite
Text
Oswald et al. "Fast and Globally Optimal Single View Reconstruction of Curved Objects." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012. doi:10.1109/CVPR.2012.6247718Markdown
[Oswald et al. "Fast and Globally Optimal Single View Reconstruction of Curved Objects." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012.](https://mlanthology.org/cvpr/2012/oswald2012cvpr-fast/) doi:10.1109/CVPR.2012.6247718BibTeX
@inproceedings{oswald2012cvpr-fast,
title = {{Fast and Globally Optimal Single View Reconstruction of Curved Objects}},
author = {Oswald, Martin R. and Töppe, Eno and Cremers, Daniel},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2012},
pages = {534-541},
doi = {10.1109/CVPR.2012.6247718},
url = {https://mlanthology.org/cvpr/2012/oswald2012cvpr-fast/}
}