Cited by 191Emotion and Mood RecognitionFace and Expression RecognitionFace recognition and analysis

Affect Recognition from Face and Body: Early Fusion vs. Late Fusion

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Gunes, H., Piccardi, M.·2006·2005 IEEE International Conference on Systems, Man and Cybernetics

Abstract

This paper presents an approach to automatic visual emotion recognition from two modalities: face and body. Firstly, individual classifiers are trained from individual modalities. Secondly, we fuse facial expression and affective body gesture information first at a feature-level, in which the data from both modalities are combined before classification, and later at a decision-level, in which we integrate the outputs of the monomodal systems by the use of suitable criteria. We then evaluate these two fusion approaches, in terms of performance over monomodal emotion recognition based on facial expression modality only. In the experiments performed the emotion classification using the two modalities achieved a better recognition accuracy outperforming the classification using the individual facial modality. Moreover, fusion at the feature-level proved better recognition than fusion at the decision-level.

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Authors
Gunes, H., & Piccardi, M.
Affiliations
University of Technology Sydney (AU)
Venue
2005 IEEE International Conference on Systems, Man and Cybernetics
Publisher
IEEE
Published
2006-01-18
Volume
4
Pages
3437-3443
ISSN
1062-922X (ISSN-L)
OpenAlex
W1587447546
Cited by
191
References
29
Citations by year
2026: 8 · 2025: 9 · 2024: 17 · 2023: 13 · 2022: 14 · 2021: 17 · 2020: 14 · 2019: 21 · 2018: 13 · 2017: 5 · 2016: 6 · 2015: 14 · 2014: 7 · 2013: 6 · 2012: 3
FWCI
11.27
Type
conference paper
Language
en
Open access
Locations
  • Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics (publishedVersion)
  • UTS ePRESS (University of Technology Sydney) (submittedVersion)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
Keywords
affect recognition, visual emotion recognition, facial expressions, body gestures, multimodal fusion, feature-level fusion, decision fusion

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