Name
Abstract | ||
|---|---|---|
This paper introduces a new idea in describing people using their first names, i.e., the name assigned at birth. We show that describing people in terms of similarity to a vector of possible first names is a powerful description of facial appearance that can be used for face naming and building facial attribute classifiers. We build models for 100 common first names used in the United States and for each pair, construct a pair wise first-name classifier. These classifiers are built using training images downloaded from the Internet, with no additional user interaction. This gives our approach important advantages in building practical systems that do not require additional human intervention for labeling. We use the scores from each pair wise name classifier as a set of facial attributes. We show several surprising results. Our name attributes predict the correct first names of test faces at rates far greater than chance. The name attributes are applied to gender recognition and to age classification, outperforming state-of-the-art methods with all training images automatically gathered from the Internet. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CVPR.2013.432 | CVPR |
Keywords | Field | DocType |
facial attribute classifiers,facial appearance,first names,facial attribute classifier,united states,face recognition,facial attribute,pair wise first-name classifier,pair wise name classifier,training image,name attribute,training images,image classification,internet,additional human intervention,facial attributes,additional user interaction,vectors,support vector machines,accuracy,computational modeling,face | Computer vision,Facial recognition system,Pattern recognition,Computer science,Artificial intelligence,Contextual image classification,Classifier (linguistics),The Internet | Conference |
Volume | Issue | ISSN |
2013 | 1 | 1063-6919 |
Citations | PageRank | References |
11 | 0.80 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huizhong Chen | 1 | 253 | 11.32 |
| andrew c gallagher | 2 | 720 | 32.17 |
| Bernd Girod | 3 | 8988 | 1062.96 |