SEWA DB: A rich database for audio-visual emotion and sentiment research in the wild
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Natural human-computer interaction and audio-visual human behaviour sensing systems, which would achieve robust performance in-the-wild are more needed than ever as digital devices are becoming indispensable part of our life more and more. Accurately annotated real-world data are the crux in devising such systems. However, existing databases usually consider controlled settings, low demographic variability, and a single task. In this paper, we introduce the SEWA database of more than 2000 minutes of audio-visual data of 398 people coming from six cultures, 50% female, and uniformly spanning the age range of 18 to 65 years old. Subjects were recorded in two different contexts: while watching adverts and while discussing adverts in a video chat. The database includes rich annotations of the recordings in terms of facial landmarks, facial action units (FAU), various vocalisations, mirroring, and continuously valued valence, arousal, liking, agreement, and prototypic examples of (dis)liking. This database aims to be an extremely valuable resource for researchers in affective computing and automatic human sensing and is expected to push forward the research in human behaviour analysis, including cultural studies. Along with the database, we provide extensive baseline experiments for automatic FAU detection and automatic valence, arousal and (dis)liking intensity estimation.
Date Issued
2021-03-01
Date Acceptance
2019-10-01
Citation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43 (3), pp.1022-1040
ISSN
0162-8828
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1022
End Page
1040
Journal / Book Title
IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume
43
Issue
3
Copyright Statement
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Commission of the European Communities
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/31581074
Grant Number
645094
Subjects
cs.HC
cs.HC
cs.AI
cs.CV
0801 Artificial Intelligence and Image Processing
0806 Information Systems
0906 Electrical and Electronic Engineering
Artificial Intelligence & Image Processing
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2019-10-01