Name
Abstract | ||
|---|---|---|
This paper presents a fully automatic system that recovers 3D face models from sequences of facial images. Unlike most 3D Morphable Model (3DMM) fitting algorithms that simultaneously reconstruct the shape and texture from a single input image, our approach builds on a more efficient least squares method to directly estimate the 3D shape from sparse 2D landmarks, which are localized by face alignment algorithms. The inconsistency between self-occluded 2D and 3D feature positions caused by head pose is ad-dressed. A novel framework to enhance robustness across multiple frames selected based on their 2D landmarks combined with individual self-occlusion handling is proposed. Evaluation on groundtruth 3D scans shows superior shape and pose estimation over previous work. The whole system is also evaluated on an “in the wild” video dataset [12] and delivers personalized and realistic 3D face shape and texture models under less constrained conditions, which only takes seconds to process each video clip. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/AVSS.2014.6918653 | AVSS |
Keywords | Field | DocType |
automatic 3d face model reconstruction,video signal processing,fast 3d face model reconstruction,3d morphable model fitting algorithms,face recognition,head pose estimation,image shape reconstruction,self-occluded 2d feature positions,multiple frames,3d feature positions,video clip,video dataset,3dmm fitting algorithms,face alignment algorithms,pose estimation,sparse 2d landmarks,shape estimation,image reconstruction,least squares approximations,robust 3d face model reconstruction,image sequences,groundtruth 3d scans,image texture reconstruction,self-occlusion handling,facial image sequences,image texture,least square method | Least squares,Computer vision,Pattern recognition,Computer science,Pose,Robustness (computer science),Artificial intelligence,Model reconstruction | Conference |
Citations | PageRank | References |
9 | 0.45 | 17 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chengchao Qu | 1 | 34 | 5.89 |
| Eduardo Monari | 2 | 68 | 6.47 |
| Tobias Schuchert | 3 | 93 | 12.21 |
| Jürgen Beyerer | 4 | 315 | 75.37 |