A Natural Visible and Infrared Facial Expression Database for Expression Recognition and Emotion Inference
By Shangfei Wang, Zhilei Liu, Siliang Lv, Yanpeng Lv, Guobing Wu, Peng Peng, Fei Chen, Xufa Wang. IEEE transactions on multimedia, 2010
365 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Social Psychology
View Paper: https://www.semanticscholar.org/paper/9c5417d273004a3e0d5de757a1fc3cced009a64d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Mohammad H. Mahoor
- Qiang Ji
- Jeffrey F. Cohn
- Lijun Yin
- Yue Wu
- Tadas Baltrusaitis
- Michael J. Reale
- Umur Aybars Ciftci
In Experimental and Cognitive Psychology
- Mohammad H. Mahoor
- Qiang Ji
- Jeffrey F. Cohn
- Lijun Yin
- Umur Aybars Ciftci
- Huiyuan Yang
- Yue Wu
- Michael J. Reale
In Social Psychology
Citations in the corpus
- DISFA: A Spontaneous Facial Action Intensity Database (2013, methodology): “NVIE [54] - 215 Student (age 17-31 yrs) - Basic facial expressions - Posed & Spontaneous - Visible and infrared imaging - Temporal analysis for posed data - Available for scientific applications UNBC-McMaster - 129 Participants (63 male,66 female) - Pain related AUs coded - Spontaneous Pain Archive ”
- BP4D-Spontaneous: a high-resolution spontaneous 3D dynamic facial expression database (2014, background): “Recent efforts to collect, annotate, and analyze spontaneous facial expression for community use have begun [26] [27] [28].”
- Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis (2016, methodology): “We further compared the two methods on randomly selected 22 subjects from USTC-NVIE database [30] and achieved recognition accuracy 71% and 59%, respectively, on classifying six prototype expressions.”