Learning of facial gestures using SVMs

Jacky Baltes, Stela Seo, Chi Tai Cheng, M. C. Lau, John Anderson

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

Abstract

This paper describes the implementation of a fast and accurate gesture recognition system. Image sequences are used to train a standard SVM to recognize Yes, No, and Neutral gestures from different users. We show that our system is able to detect facial gestures with more than 80% accuracy from even small input images.

Original languageEnglish
Title of host publicationNext Wave in Robotics - 14th FIRA RoboWorld Congress, FIRA 2011, Proceedings
Pages147-154
Number of pages8
DOIs
Publication statusPublished - 2011 Sep 20
Event14th FIRA RoboWorld Congress on Next Wave in Robotics, FIRA 2011 - Kaohsiung, Taiwan
Duration: 2011 Aug 262011 Aug 30

Publication series

NameCommunications in Computer and Information Science
Volume212 CCIS
ISSN (Print)1865-0929

Other

Other14th FIRA RoboWorld Congress on Next Wave in Robotics, FIRA 2011
CountryTaiwan
CityKaohsiung
Period11/8/2611/8/30

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Keywords

  • Facial Recognition
  • Machine Learning
  • SVM

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

Cite this

Baltes, J., Seo, S., Cheng, C. T., Lau, M. C., & Anderson, J. (2011). Learning of facial gestures using SVMs. In Next Wave in Robotics - 14th FIRA RoboWorld Congress, FIRA 2011, Proceedings (pp. 147-154). (Communications in Computer and Information Science; Vol. 212 CCIS). https://doi.org/10.1007/978-3-642-23147-6_18