Tensor-Based Non-Rigid Structure from Motion

2022 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2022)(2022)

引用 3|浏览3
暂无评分
摘要
In this work we present a method that combines tensor-based face modelling and analysis and non-rigid structure-from-motion (NRSFM). The core idea is to see that the conventional tensor formulation for the face structure and expression analysis can be utilised while the structure component can be directly analysed as the non-rigid structure-from-motion problem. To the NRSFM problem part we further present a novel prior-free approach that factorises the 2D input shapes into affine projection matrices, rank-one 3D affine basis shapes, and the basis shape coefficients. The linear combination of the basis shapes thus yields the recovered 3D shapes upto an affine transformation. In contrast to most works in literature, no calibration information of the cameras or structure prior is required. Experiments on challenging face datasets show that our method, with and without the metric upgrade, is accurate and fast when compared to the state-of-the-art and is well suitable for dense reconstruction and face editing.
更多
查看译文
关键词
3D Computer Vision Computational Photography,Image and Video Synthesis,Datasets,Evaluation and Comparison of Vision Algorithms,Statistical Methods,Learning and Optimization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要