Template-Free 3D Reconstruction of Poorly-Textured Nonrigid Surfaces
Abstract
Two main classes of approaches have been studied to perform monocular nonrigid 3D reconstruction: Template-based methods and Non-rigid Structure from Motion techniques. While the first ones have been applied to reconstruct poorly-textured surfaces, they assume the availability of a 3D shape model prior to reconstruction. By contrast, the second ones do not require such a shape template, but, instead, rely on points being tracked throughout a video sequence, and are thus ill-suited to handle poorly-textured surfaces. In this paper, we introduce a template-free approach to reconstructing a poorly-textured, deformable surface. To this end, we leverage surface isometry and formulate 3D reconstruction as the joint problem of non-rigid image registration and depth estimation. Our experiments demonstrate that our approach yields much more accurate 3D reconstructions than state-of-the-art techniques.
Cite
Text
Wang et al. "Template-Free 3D Reconstruction of Poorly-Textured Nonrigid Surfaces." European Conference on Computer Vision, 2016. doi:10.1007/978-3-319-46478-7_40Markdown
[Wang et al. "Template-Free 3D Reconstruction of Poorly-Textured Nonrigid Surfaces." European Conference on Computer Vision, 2016.](https://mlanthology.org/eccv/2016/wang2016eccv-template/) doi:10.1007/978-3-319-46478-7_40BibTeX
@inproceedings{wang2016eccv-template,
title = {{Template-Free 3D Reconstruction of Poorly-Textured Nonrigid Surfaces}},
author = {Wang, Xuan and Salzmann, Mathieu and Wang, Fei and Zhao, Jizhong},
booktitle = {European Conference on Computer Vision},
year = {2016},
pages = {648-663},
doi = {10.1007/978-3-319-46478-7_40},
url = {https://mlanthology.org/eccv/2016/wang2016eccv-template/}
}