@inproceedings{87636076a77147fa8f1c522dc690e3cf,
title = "Predicting occupation from single facial images",
abstract = "Facial images embed age, gender, and other rich information that is implicitly related to occupation. In this work, we advocate that occupation prediction from a single facial image is a doable research direction. We first extract visual features from multiple levels of patches and describe them by locality-constrained linear coding. To avoid the curse of dimensionality and over fitting, a boost strategy called multi-feature SVM is used to integrate features. Intra-class and inter-class visual variations are jointly considered in the boosting framework to further improve performance. In the evaluation, we verify that this is a promising research topic with encouraging performance, and also discuss interesting issues from various perspectives.",
author = "Chu, {Wei Ta} and Chiu, {Chih Hao}",
year = "2015",
month = feb,
day = "5",
doi = "10.1109/ISM.2014.13",
language = "English",
series = "Proceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "9--12",
booktitle = "Proceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014",
address = "United States",
note = "16th IEEE International Symposium on Multimedia, ISM 2014 ; Conference date: 10-12-2014 Through 12-12-2014",
}