A Large Video Database for Computational Models of Induced Emotion

Yoann Baveye 1 Jean-Noël Bettinelli 1 Emmanuel Dellandréa 1 Liming Chen 1 Christel Chamaret 2
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 Technicolor R & I [Cesson Sévigné]
Abstract : To contribute to the need for emotional databases and affective tagging, the LIRIS-ACCEDE is proposed in this paper. LIRIS-ACCEDE is an Annotated Creative Commons Emotional DatabasE composed of 9800 video clips extracted from 160 movies shared under Creative Commons licenses. It allows to make this database publicly available1 without copyright issues. The 9800 video clips (each 8-12 seconds long) are sorted along the induced valence axis, from the video perceived the most negatively to the video perceived the most positively. The annotation was carried out by 1518 annotators from 89 different countries using crowdsourcing. A baseline late fusion scheme using ground truth from annotations is computed to predict emotion categories in video clips.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01339226
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Wednesday, June 29, 2016 - 3:49:31 PM
Last modification on : Thursday, November 21, 2019 - 2:24:23 AM

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CNRS | EC-LYON | UNIV-LYON2 | LIRIS | INSA-LYON | UNIV-LYON1 | INSA-GROUPE | LABEXIMU | UDL

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Yoann Baveye, Jean-Noël Bettinelli, Emmanuel Dellandréa, Liming Chen, Christel Chamaret. A Large Video Database for Computational Models of Induced Emotion. 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII), Sep 2013, Geneva, Switzerland. pp.13-18, ⟨10.1109/ACII.2013.9⟩. ⟨hal-01339226⟩

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