Synthesis of Multiple Pose Facial Images Using Tensor-Based Subspace Learning Method
Abstract
Facial pose synthesis has many useful applications in practice. How to synthesize facial pose images robustly and simply is still a challenging problem. In this paper we proposed a tensor-based subspace learning method (TSL) that makes possible the synthesis of human multi-pose facial images from a single 2D image. We organize 2D multi-pose images in a tensor form and apply tensor decomposition to build a projection subspace. An input 2D image is projected into the projection subspace to get a corresponding identity vector. The identity vector is used to generate the novel pose images. The experiments are performed on MaVIC (KAO-Ritsumeikan Multi-angle View, Illumination and Cosmetic Facial Database) and preliminary experimental results show the effectiveness of our proposed method.
Cite
Text
Qiao et al. "Synthesis of Multiple Pose Facial Images Using Tensor-Based Subspace Learning Method." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457697Markdown
[Qiao et al. "Synthesis of Multiple Pose Facial Images Using Tensor-Based Subspace Learning Method." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/qiao2009iccvw-synthesis/) doi:10.1109/ICCVW.2009.5457697BibTeX
@inproceedings{qiao2009iccvw-synthesis,
title = {{Synthesis of Multiple Pose Facial Images Using Tensor-Based Subspace Learning Method}},
author = {Qiao, Xu and Chen, Yen-Wei and Han, Xian-Hua and Igarashi, Takanori and Nakao, Keisuke},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2009},
pages = {219-226},
doi = {10.1109/ICCVW.2009.5457697},
url = {https://mlanthology.org/iccvw/2009/qiao2009iccvw-synthesis/}
}