The shortage of emotion-annotated video datasets suitable for training and validating machine learning models for facial expression-based emotion recognition stems primarily from the significant effort and cost required for manual annotation. In this paper, we present AffecTube as a comprehensive solution that leverages crowdsourcing to annotate videos directly on the YouTube platform, resulting in ready-to-use emotion-annotated datasets. AffecTube provides a low-resource environment with an intuitive interface and customizable options, making it a versatile tool applicable not only to emotion annotation, but also to various video-based behavioral annotation processes.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1016/j.softx.2023.101504
- Category
- Publikacja w czasopiśmie
- Type
- artykuły w czasopismach
- Language
- angielski
- Publication year
- 2023
