The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis
Abstract
Emotion is expressed in multiple modalities, yet most research has considered at most one or two. This stems in part from the lack of large, diverse, well-annotated, multimodal databases with which to develop and test algorithms. We present a well-annotated, multimodal, multidimensional spontaneous emotion corpus of 140 participants. Emotion inductions were highly varied. Data were acquired from a variety of sensors of the face that included high-resolution 3D dynamic imaging, high-resolution 2D video, and thermal (infrared) sensing, and contact physiological sensors that included electrical conductivity of the skin, respiration, blood pressure, and heart rate. Facial expression was annotated for both the occurrence and intensity of facial action units from 2D video by experts in the Facial Action Coding System (FACS). The corpus further includes derived features from 3D, 2D, and IR (infrared) sensors and baseline results for facial expression and action unit detection. The entire corpus will be made available to the research community.
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What are emotions? And how can they be measured?
Scherer, K. R. (2005) · Social Science Information · doi:10.1177/0539018405058216 · Cited by 4,264
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797
A 3D Facial Expression Database For Facial Behavior Research
Yin, L., Wei, X., Sun, Y., Wang, J., & Rosato, M. J. (2006) · 7th International Conference on Automatic Face and Gesture Recognition (FGR06) · doi:10.1109/fgr.2006.6 · Cited by 1,171
Self-citationMcKeown, G., Valstar, M., Cowie, R., Pantic, M., & Schroder, M. (2012) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.20 · Cited by 665
Wang, S., Liu, Z., Lv, S., Lv, Y., Wu, G., Peng, P., Chen, F., & Wang, X. (2010) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2010.2060716 · Cited by 397
Static and dynamic 3D facial expression recognition: A comprehensive survey
Sandbach, G., Zafeiriou, S., Pantic, M., & Yin, L. (2012) · Image and Vision Computing · doi:10.1016/j.imavis.2012.06.005 · Cited by 357
Self-citationFERA 2015 - second Facial Expression Recognition and Analysis challenge
Valstar, M. F., Almaev, T., Girard, J. M., McKeown, G., Mehu, M., Yin, L., Pantic, M., & Cohn, J. F. (2015) · 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) · doi:10.1109/fg.2015.7284874 · Cited by 252
Self-citationAutomatic coding of facial expressions displayed during posed and genuine pain
Littlewort, G. C., Bartlett, M. S., & Lee, K. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2008.12.010 · Cited by 216
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Egger, B., Smith, W. A. P., Tewari, A., Wuhrer, S., Zollhoefer, M., Beeler, T., Bernard, F., Bolkart, T., Kortylewski, A., Romdhani, S., et al. (2020) · ACM Transactions on Graphics · doi:10.1145/3395208 · Cited by 448
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Liang, T., Lin, G., Feng, L., Zhang, Y., & Lv, F. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00804 · Cited by 93
Nowara, E. M., McDuff, D., & Veeraraghavan, A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw50498.2020.00150 · Cited by 66
Metadata
- Authors
- Zhang, Z., Girard, J. M., Wu, Y., Zhang, X., Liu, P., Ciftci, U., Canavan, S., Reale, M., Horowitz, A., Yang, H., Cohn, J. F., Ji, Q., & Yin, L.
- Venue
- 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2016-06
- Pages
- 3438-3446
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2470957930
- Cited by
- 424
- References
- 8
- FWCI
- 34.06
- Type
- conference paper
- Language
- en
- Open access
- closed
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