@inproceedings{5006b17d49814c22bdac0a4a4612d810,
title = "A Probabilistic Fusion Approach to human age prediction",
abstract = "Human age prediction is useful for many applications. The age information could be used as a kind of semantic knowledge for multimedia content analysis and understanding. In this paper we propose a Probabilistic Fusion Approach (PFA) that produces a high performance estimator for human age prediction. The PFA framework fuses a re-gressor and a classifier. We derive the predictor based on Hayes' rule without the mutual independence assumption that is very common for traditional classifier combination methods. Using a sequential fusion strategy the predictor reduces age estimation errors significantly. Experiments on the large UIUC-IFP-Yaging database and the FG-NET aging database show the merit of the proposed approach to human age prediction.",
author = "Guodong Guo and Yun Fu and Dyer, {Charles R.} and Huang, {Thomas S.}",
year = "2008",
doi = "10.1109/CVPRW.2008.4563041",
language = "English (US)",
isbn = "9781424423408",
series = "2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops",
booktitle = "2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops",
note = "2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops ; Conference date: 23-06-2008 Through 28-06-2008",
}