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Cited by 417

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Facial Action Recognition for Facial Expression Analysis From Static Face Images

Open access
Pantic, M., Rothkrantz, L.J.M.·2004·IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)

Abstract

Automatic recognition of facial gestures (i.e., facial muscle activity) is rapidly becoming an area of intense interest in the research field of machine vision. In this paper, we present an automated system that we developed to recognize facial gestures in static, frontal- and/or profile-view color face images. A multidetector approach to facial feature localization is utilized to spatially sample the profile contour and the contours of the facial components such as the eyes and the mouth. From the extracted contours of the facial features, we extract ten profile-contour fiducial points and 19 fiducial points of the contours of the facial components. Based on these, 32 individual facial muscle actions (AUs) occurring alone or in combination are recognized using rule-based reasoning. With each scored AU, the utilized algorithm associates a factor denoting the certainty with which the pertinent AU has been scored. A recognition rate of 86% is achieved.

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Metadata

Authors
Pantic, M., & Rothkrantz, L. J. M.
Venue
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics)
Published
2004-06
Volume
34
Issue
3
Pages
1449-1461
ISSN
1083-4419 (ISSN-L)
OpenAlex
W2140351517
Cited by
417
References
28
FWCI
14.94
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Facial Action Recognition for Facial Expression Analysis From Static Face Images. https://app.cochat.ai/papers/10.1109/tsmcb.2004.825931
The paper
Pantic, M., & Rothkrantz, L. J. M. (2004). Facial Action Recognition for Facial Expression Analysis From Static Face Images. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics). https://doi.org/10.1109/tsmcb.2004.825931

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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