Estimating Age, Gender, and Identity using First Name Priors

Is it possible to recognize people for which no labeled examples exist? This image contains Mildred and Lisa. Mildred, a first name popular in the early 20th century, is the older woman on the right, while Lisa is the younger woman on the left. This recognition is possible for humans because of their extensive cultural training. Our algorithm takes advantage of this context as well. (Image source)

Abstract
Recognizing people in images is one of the foremost challenges in computer vision. It is important to remember that consumer photography has a highly social aspect. The photographer captures images not in a random fashion, but rather to remember or document meaningful events in her life. The culture of the society of which the photographer is a part provides a strong context for recognizing the content of the captured images.

We demonstrate one aspect of this cultural context by recognizing people from first names. The distribution of first names chosen for newborn babies evolves with time and is gender-specific. As a result, a first name provides a strong prior for describing the individual. Specifically, we use the U.S. Social Security Administration baby name database to learn priors for gender and age for 6693 first names. Most face recognition methods do not even consider the name of the individual of interest, or the name is treated merely as an identifier that provides no information about appearance. In contrast, we combine image-based gender and age classifiers with the cultural context information provided by first names to recognize people with no labeled examples. Our model uses image-based age and gender estimates for assigning first names to people and in turn, the age and gender estimates are improved.

Test Set
The Test Image Set

People
Andrew Gallagher
Tsuhan Chen

Citation
A. Gallagher, T. Chen, "Estimating Age, Gender and Identity using First Name Priors," IEEE Conference on Computer Vision and Pattern Recognition 2008.

Bibtex

@inproceedings{gallagher_cvpr_08_names,

author = {A. Gallagher and T. Chen},

title = {Estimating Age, Gender and Identity using First Name Priors},

booktitle = {Proc. CVPR},

year = {2008},

}