Predicting occupation from single facial images

Wei Ta Chu, Chih Hao Chiu

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

3 Citations (Scopus)


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.
Number of pages4
ISBN (Electronic)9781479943111
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


Conference16th IEEE International Symposium on Multimedia, ISM 2014

All Science Journal Classification (ASJC) codes

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

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