Facial analysis aided human gesture recognition for Human Computer Interaction

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

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

Abstract

Human gesture recognition systems are natural to use for achieving intelligent Human Computer Interaction (HCI). These systems should memorize the specific user and enable the user to gesture naturally without wearing special devices. Extracting different components of visual actions from human gestures, such as shape and motion of hand- facial expression and torso, is the key tasks in gesture recognition. So far, in the field of gesture n-cognition. most of the previous work have focused only on hand motion features and required the user lo wear special devices. In this paper, we present, an appearance-based multimodal gesture recognition framework, which combines the different modalities of features such as face identity, facial expression and hand motions which have been extracted from the image frames captured directly by a web camera. We refer 12 classes of human gestures with facial expression including neutral, negative (e.g. "angry") and positive (e.g. "excited") meanings from American Sign Language. A condensation-based algorithm is adopted for classification. We collected a data set with three recording sessions and conducted experiments with different combination techniques. Experimental results showed that the performance of hand gesture recognition is improved by adding facial analysis.

Original languageEnglish
Title of host publicationProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
Pages446-449
Number of pages4
Publication statusPublished - 2011 Dec 1
Event12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan
Duration: 2011 Jun 132011 Jun 15

Publication series

NameProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Conference

Conference12th IAPR Conference on Machine Vision Applications, MVA 2011
CountryJapan
CityNara
Period11/6/1311/6/15

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Luo, D., Gao, H., Ekenel, H. K., & Ohya, J. (2011). Facial analysis aided human gesture recognition for Human Computer Interaction. In Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011 (pp. 446-449). (Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011).