Automatic annotation of facial actions from a video record: The case of eyebrows raising and frowning

Abstract : Recent advances in the field of computer vision and machine learning have given birth to a generation of softwares enable to detect and track a face along a video record and eventually to measure its internal facial movements. We investigate herein on a specific task, the detection of eyebrows raising and frowning facial actions, the potential of these softwares on spontaneous, in-the-wild video corpus. We propose a tool which allow to extract eyebrows raising and frowning from the output of two state-of-the-art facial behavior analysis softwares (OpenFace and IntraFace). The evaluation performed on our manually annotated in-the-wild video corpus suggests that the tool can be used with benefits for automatic annotation purpose.
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Communication dans un congrès
Workshop on "Affects, Compagnons Artificiels et Interactions", WACAI 2018, Jun 2018, Porquerolles, France. 7 p., 2018, 〈http://www.lsis.org/wacai2018/〉
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Soumis le : mercredi 18 avril 2018 - 11:49:07
Dernière modification le : samedi 28 avril 2018 - 01:22:52

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Stéphane Rauzy, Aurélie Goujon. Automatic annotation of facial actions from a video record: The case of eyebrows raising and frowning. Workshop on "Affects, Compagnons Artificiels et Interactions", WACAI 2018, Jun 2018, Porquerolles, France. 7 p., 2018, 〈http://www.lsis.org/wacai2018/〉. 〈hal-01769684〉

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