Learning of facial gestures using SVMs

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

*Corresponding author for this work

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


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
Number of pages8
Publication statusPublished - 2011
Externally publishedYes
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


Other14th FIRA RoboWorld Congress on Next Wave in Robotics, FIRA 2011


  • Facial Recognition
  • Machine Learning
  • SVM

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


Dive into the research topics of 'Learning of facial gestures using SVMs'. Together they form a unique fingerprint.

Cite this