Detection of Gaze States: Fixation or Motion

Author

Wang, Xianmei ; Li, Cheng ; Zheng, Siyi ; Wang, Zhiliang

Author_Institution

Sch. of Comput. & Commun. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2012

fDate

23-25 Nov. 2012

Firstpage

167

Lastpage

170

Abstract

This paper addresses the problem of automated analysis of gaze states (fixation or motion). First, we present a novel dynamic and multi-level analysis structure for the detection of gaze states based on eye action units (AUs). Then the eye action units are analyzed both in spatial and temporal domain. And finally these eye AUs form the input to infer eye gaze state by employing Hidden Markov Models (HMMs) classifiers. The experimental results demonstrated reliable recognition of gaze states.

Keywords

emotion recognition; eye; face recognition; hidden Markov models; image classification; HMM; automated gaze state analysis; dynamic analysis structure; expression recognition; eye action units; facial expression recognition; fixation; gaze state detection; hidden Markov models classifiers; motion; multilevel analysis structure; spatial domain; temporal domain; Accuracy; Computational modeling; Face recognition; Feature extraction; Gold; Hidden Markov models; Iris recognition; HMMs; action units; facial expression recognition; gaze state;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Home (ICDH), 2012 Fourth International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4673-1348-3

Type

conf

DOI

10.1109/ICDH.2012.20

Filename

6376404