Detection of asymmetric eye action units in spontaneous videos
Name
Mikhail-2009-Detection of asymmetric eye action units in spontaneous videos.pdf
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207.76 KB
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Author(s)
el Kaliouby, Rana
Mikhail, Mina
Date Issued
January 2010
Journal
16th IEEE International Conference on Image Processing (ICIP), 2009
Publisher
Institute of Electrical and Electronics Engineers
Citation
Mikhail, M., and R. el Kaliouby. “Detection of asymmetric eye action units in spontaneous videos.” Image Processing (ICIP), 2009 16th IEEE International Conference on. 2009. 3557-3560. © 2010 IEEE
Version
Final published version
Abstract
With recent advances in machine vision, automatic detection of human expressions in video is becoming important especially because human labeling of videos is both tedious and error prone. In this paper, we present an approach for detecting facial expressions based on the Facial Action Coding System (FACS) in spontaneous videos. We present an automated system for detecting asymmetric eye open (AU41) and eye closed (AU43) actions. We use Gabor Jets to select distinctive features from the image and compare between three different classifiers-Bayesian networks, Dynamic Bayesian networks and Support Vector Machines-for classification. Experimental evaluation on a large corpus of spontaneous videos yielded an average accuracy of 98% for eye closed (AU43), and 92.75% for eye open (AU41).
MIT Department
Massachusetts Institute of Technology. Media Laboratory
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/ICIP.2009.5414341
