NDLI: Texture and Shape Information Fusion for Facial Action Unit Recognition

Content Provider	IEEE Xplore Digital Library
Author	Kotsia, I. Zafeiriou, S. Nikolaidis, N. Pitas, I.
Copyright Year	2008
Description	Author affiliation: Aristotle Univ. of Thessaloniki, Thessaloniki (Kotsia, I.; Zafeiriou, S.; Nikolaidis, N.; Pitas, I.)
Abstract	A novel method that fuses texture and shape information to achieve Facial Action Unit (FAU) recognition from video sequences is proposed. In order to extract the texture information, a subspace method based on Discriminant Non- negative Matrix Factorization (DNMF) is applied on the difference images of the video sequence, calculated taking under consideration the neutral and the most expressive frame, to extract the desired classification label. The shape information consists of the deformed Candide facial grid (more specifically the grid node displacements between the neutral and the most expressive facial expression frame) that corresponds to the facial expression depicted in the video sequence. The shape information is afterwards classified using a two-class Support Vector Machine (SVM) system. The fusion of texture and shape information is performed using Median Radial Basis Functions (MRBFs) Neural Networks (NNs) in order to detect the set of present FAUs. The accuracy achieved in the Cohn-Kanade database is equal to 92.1% when recognizing the 17 FAUs that are responsible for facial expression development.
Starting Page	77
Ending Page	82
File Size	1779367
Page Count	6
File Format	PDF
ISBN	9780769530864
DOI	10.1109/ACHI.2008.26
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-02-10
Publisher Place	Martinique
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Fuses Facial Action Unit Recognition Face recognition Video sequences Image sequences Data mining Support Vector Machines Support vector machines Radial Basis Functions Neural Networks Neural networks Support vector machine classification Discriminant Non-negative Matrix Factorization Informatics Fusion
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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