Multilinear Pose and Body Shape Estimation of Dressed Subjects from Image Sets
Abstract
In this paper we propose a multilinear model of human pose and body shape which is estimated from a database of registered 3D body scans in different poses. The model is generated by factorizing the measurements into pose and shape dependent components. By combining it with an ICP based registration method, we are able to estimate pose and body shape of dressed subjects from single images. If several images of the subject are available, shape and poses can be optimized simultaneously for all input images. Additionally, while estimating pose and shape, we use the model as a virtual calibration pattern and also recover the parameters of the perspective camera model the images were created with.
Cite
Text
Hasler et al. "Multilinear Pose and Body Shape Estimation of Dressed Subjects from Image Sets." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010. doi:10.1109/CVPR.2010.5539853Markdown
[Hasler et al. "Multilinear Pose and Body Shape Estimation of Dressed Subjects from Image Sets." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010.](https://mlanthology.org/cvpr/2010/hasler2010cvpr-multilinear/) doi:10.1109/CVPR.2010.5539853BibTeX
@inproceedings{hasler2010cvpr-multilinear,
title = {{Multilinear Pose and Body Shape Estimation of Dressed Subjects from Image Sets}},
author = {Hasler, Nils and Ackermann, Hanno and Rosenhahn, Bodo and Thormählen, Thorsten and Seidel, Hans-Peter},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2010},
pages = {1823-1830},
doi = {10.1109/CVPR.2010.5539853},
url = {https://mlanthology.org/cvpr/2010/hasler2010cvpr-multilinear/}
}