We propose a novel dataset for studying and modeling facial expression intensity. Facial expression intensity recognition is a rarely discussed challenge, likely stemming from a lack of suitable datasets. Our dataset has been created by extracting facial expressions from actors across twelve fiction films, followed by crowd-sourced online annotation of the expression intensity and variability levels. It consists of over 400 automatically extracted video segments ranging from 3 to 5 seconds, as well as annotations and facial landmarks. We also present preliminary statistics derived from this dataset.

Towards the dataset for analysis and recognition of facial expressions intensity

Niewiadomski R.
2024-01-01

Abstract

We propose a novel dataset for studying and modeling facial expression intensity. Facial expression intensity recognition is a rarely discussed challenge, likely stemming from a lack of suitable datasets. Our dataset has been created by extracting facial expressions from actors across twelve fiction films, followed by crowd-sourced online annotation of the expression intensity and variability levels. It consists of over 400 automatically extracted video segments ranging from 3 to 5 seconds, as well as annotations and facial landmarks. We also present preliminary statistics derived from this dataset.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1219923
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