A Large Video Database for Computational Models of Induced Emotion

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.
Type de document :
Communication dans un congrès
2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII), Sep 2013, Geneva, Switzerland. pp.13-18, 2013, 〈10.1109/ACII.2013.9〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01339226
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : mercredi 29 juin 2016 - 15:49:31
Dernière modification le : vendredi 10 novembre 2017 - 01:20:13

Identifiants

Collections

Citation

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, 2013, 〈10.1109/ACII.2013.9〉. 〈hal-01339226〉

Partager

Métriques

Consultations de la notice

117