Predicting occupation from single facial images

Wei Ta Chu, Chih Hao Chiu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9-12
Number of pages4
ISBN (Electronic)9781479943111
DOIs
Publication statusPublished - 2015 Feb 5
Event16th IEEE International Symposium on Multimedia, ISM 2014 - Taichung, Taiwan
Duration: 2014 Dec 102014 Dec 12

Publication series

NameProceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014

Conference

Conference16th IEEE International Symposium on Multimedia, ISM 2014
CountryTaiwan
CityTaichung
Period14-12-1014-12-12

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software
  • Media Technology

Cite this

Chu, W. T., & Chiu, C. H. (2015). Predicting occupation from single facial images. In Proceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014 (pp. 9-12). [7032946] (Proceedings - 2014 IEEE International Symposium on Multimedia, ISM 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISM.2014.13