Name
Abstract | ||
|---|---|---|
In this paper, a novel scheme is introduced for human facial feature extraction. Unlike previous methods that fit a 3D morphable model to 2D intensity images, our scheme utilizes 3D range images to extract features without requiring manually-defined initial landmark points. A linear transformation is used to achieve the mapping between the 3D model and a 3D range image, which makes the computation simple and fast. Moreover, our scheme is robust to the illumination and pose variations. In addition to features from range images, extra features can be obtained by examining optional 2D texture images. Using our scheme, we can also perform automatic eye/mouth corner localization. Experimental results show the high accuracy and robustness of our scheme. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.366217 | ICASSP (2) |
Keywords | Field | DocType |
2d intensity images,face recognition,feature extraction,image morphing,optional 2d texture images,3d morphable model,linear transformation,geometric modeling,computer vision,extra features,automatic eye-mouth corner localization,pose variations,facial feature extraction,range images,image texture,illumination,human facial,lighting,data mining,geometric model,robustness,digital images,shape | Facial recognition system,Computer vision,Pattern recognition,Image texture,Computer science,Feature (computer vision),Geometric modeling,Feature extraction,Robustness (computer science),Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Landmark | Conference |
Volume | ISSN | ISBN |
2 | 1520-6149 E-ISBN : 1-4244-0728-1 | 1-4244-0728-1 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Le Zou | 1 | 32 | 3.20 |
| S. Cheng | 2 | 548 | 27.56 |
| Zixiang Xiong | 3 | 3444 | 275.03 |
| Mi Lu | 4 | 0 | 0.34 |
| Kenneth R. Castleman | 5 | 91 | 12.80 |