Name
Abstract | ||
|---|---|---|
There is a steadily growing range of applications that can benefit from facial reconstruction techniques, leading to an increasing demand for reconstruction of high-quality 3D face models. While it is an important expressive part of the human face, the nose has received less attention than other expressive regions in the face reconstruction literature. When applying existing reconstruction methods to facial images, the reconstructed nose models are often inconsistent with the desired shape and expression. In this paper, we propose a coarse-to-fine 3D nose reconstruction and correction pipeline to build a nose model from a single image, where 3D and 2D nose curve correspondences are adaptively updated and refined. We first correct the reconstruction result coarsely using constraints of 3D-2D sparse landmark correspondences, and then heuristically update a dense 3D-2D curve correspondence based on the coarsely corrected result. A final refinement step is performed to correct the shape based on the updated 3D-2D dense curve constraints. Experimental results show the advantages of our method for 3D nose reconstruction over existing methods. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s41095-021-0237-5 | Computational Visual Media |
Keywords | DocType | Volume |
nose shape recovery, single image 3D reconstruction, contour correspondence, Laplacian deformation | Journal | 8 |
Issue | ISSN | Citations |
2 | 2096-0433 | 0 |
PageRank | References | Authors |
0.34 | 10 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tang, Yanlong | 1 | 0 | 0.34 |
| Zhang, Yun | 2 | 0 | 0.34 |
| Xiaoguang Han | 3 | 220 | 29.01 |
| Zhang, Fang-Lue | 4 | 0 | 0.34 |
| Yu-Kun Lai | 5 | 1025 | 80.48 |
| Ruofeng Tong | 6 | 466 | 49.69 |