The eNTERFACE’05 Audio-Visual Emotion Database
Abstract
This paper presents an audio-visual emotion database that can be used as a reference database for testing and evaluating video, audio or joint audio-visual emotion recognition algorithms. Additional uses may include the evaluation of algorithms performing other multimodal signal processing tasks, such as multimodal person identification or audio-visual speech recognition. This paper presents the difficulties involved in the construction of such a multimodal emotion database and the different protocols that have been used to cope with these difficulties. It describes the experimental setup used for the experiments and includes a section related to the segmentation and selection of the video samples, in such a way that the database contains only video sequences carrying the desired affective information. This database is made publicly available for scientific research purposes.
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References 10 · Cited by 615
- Authors
- Martin, O., Kotsia, I., Macq, B., & Pitas, I.
- Affiliations
- UCLouvain (BE)
- Venue
- 22nd International Conference on Data Engineering Workshops (ICDEW'06)
- Publisher
- IEEE
- Published
- 2006
- Pages
- 8-8
- OpenAlex
- W2168692779
- Cited by
- 615
- References
- 10
- Citations by year
- 2026: 18 · 2025: 39 · 2024: 62 · 2023: 61 · 2022: 61 · 2021: 69 · 2020: 48 · 2019: 43 · 2018: 32 · 2017: 30 · 2016: 28 · 2015: 31 · 2014: 16 · 2013: 18 · 2012: 13
- FWCI
- 11.98
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Data Engineering Workshops (ICDEW) (publishedVersion)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
- Funders
- Waalse Gewest
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- audio-visual emotion recognition, emotion database, multimodal emotion recognition, video segmentation, multimodal signal processing
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