Appearance-based human gesture recognition using multimodal features for human computer interaction

Dan Luo, Hua Gao, Hazim Kemal Ekenel, Jun Ohya

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

1 Citation (Scopus)

Abstract

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Human Vision and Electronic Imaging XVI
DOIs
Publication statusPublished - 2011 Apr 11
EventHuman Vision and Electronic Imaging XVI - San Francisco, CA, United States
Duration: 2011 Jan 242011 Jan 27

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7865
ISSN (Print)0277-786X

Conference

ConferenceHuman Vision and Electronic Imaging XVI
CountryUnited States
CitySan Francisco, CA
Period11/1/2411/1/27

Keywords

  • Condensation Algorithm
  • Facial Expression
  • Gesture Recognition

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Luo, D., Gao, H., Ekenel, H. K., & Ohya, J. (2011). Appearance-based human gesture recognition using multimodal features for human computer interaction. In Proceedings of SPIE-IS and T Electronic Imaging - Human Vision and Electronic Imaging XVI [786509] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7865). https://doi.org/10.1117/12.872525