Partial least squares regression on grassmannian manifold for emotion recognition
Open accessAbstract
In this paper, we propose a method for video-based human emotion recognition. For each video clip, all frames are represented as an image set, which can be modeled as a linear subspace to be embedded in Grassmannian manifold. After feature extraction, Class-specific One-to-Rest Partial Least Squares (PLS) is learned on video and audio data respectively to distinguish each class from the other confusing ones. Finally, an optimal fusion of classifiers learned from both modalities (video and audio) is conducted at decision level. Our method is evaluated on the Emotion Recognition In The Wild Challenge (EmotiW 2013). The experimental results on both validation set and blind test set are presented for comparison. The final accuracy achieved on test set outperforms the baseline by 26%.
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Because of the subtleness of facial configurations, most predesigned representations are dynamically extracting the appearance.
“Because of the subtleness of facial configurations most predesigned representations are dynamically extracting the appearance [262], [263], [264], [265].”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [264]
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“…of Intelligence Information Processing Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China {mengyi.liu, ruiping.wang, zhiwu.huang, shiguang.shan, xilin.chen}@vipl.ict.ac.cn ABSTRACT In this paper, we propose a method for video-based human emotion recognition.”
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- Authors
- Liu, M., Wang, R., Huang, Z., Shan, S., & Chen, X.
- Affiliations
- Chinese Academy of Sciences (CN)
- Venue
- Proceedings of the 15th ACM on International conference on multimodal interaction
- Publisher
- ACM
- Published
- 2013-12-09
- Pages
- 525-530
- OpenAlex
- W2123582174
- Cited by
- 62
- References
- 20
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 1 · 2021: 4 · 2020: 8 · 2019: 4 · 2018: 6 · 2017: 7 · 2016: 9 · 2015: 11 · 2014: 10
- FWCI
- 13.61
- Type
- conference paper
- Language
- en
- Open access
- Locations
- INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (publishedVersion)
- ePrints Soton (University of Southampton) (acceptedVersion)
- Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (submittedVersion, other-oa)
- Funders
- National Natural Science Foundation of China
- 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
- emotion recognition, video-based emotion recognition, Grassmannians, partial least squares regression, decision fusion, multimodal fusion
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