Name
Abstract | ||
|---|---|---|
Head pose estimation helps to align a 3D face model to a 2D image, which is critical to research requiring dense 2D-to-2D or 3D-to-2D correspondence. Traditional pose estimation relies strongly on the accuracy of landmarks, so it is sensitive to missing or incorrect landmarks. In this paper, we propose a landmark-free approach to estimate the pose projection matrix. The method can be used to estimate this matrix in unconstrained scenarios and we demonstrate its effectiveness through multiple head pose estimation experiments. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/BTAS.2015.7358799 | 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS) |
Keywords | Field | DocType |
3D dense facial model,landmark-free approach,3D face model,pose projection matrix,unconstrained scenario,multiple head pose estimation experiment | Computer vision,Pattern recognition,Computer science,Matrix (mathematics),Projection (linear algebra),3D pose estimation,Pose,Artificial intelligence,Articulated body pose estimation,Landmark | Conference |
ISSN | Citations | PageRank |
2474-9680 | 2 | 0.36 |
References | Authors | |
23 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuhang Wu | 1 | 21 | 6.11 |
| Xiang Xu | 2 | 30 | 5.58 |
| Shishir K Shah | 3 | 501 | 40.08 |
| Ioannis A. Kakadiaris | 4 | 1910 | 203.66 |