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FaceReader
Resources
Download our white papers
FaceReader product videos
FaceReader Classifications Demo
Discover the realtime modeling capabilities of FaceReader.
Affective attitudes in FaceReader
Using the Action Unit Module, FaceReader is able to detect the affective attitude 'confusion'.
Baby FaceReader
Baby FaceReader enables you to recognize the facial expressions of an infant automatically!
Download our free product overviews
What does your face say?
Curious what emotions your face shows? Upload a photo here and our FaceReader software will test it for emotionality. The better quality the picture, the better the results! To get the best results, test only photos where your face is clearly visible. The lighting should be sufficient as well.
Try it now and find out what your face says.
Customer success stories
How to measure emotions in the Uses and Acceptability Lab
Jean-Marc Diverrez, bcom Institute of Research and Technology
Sensory evaluation - Food science & technology
Prof. Susan Duncan, Virginia Tech
Social Media Lab: How people make sense of data
Tiffany Andry, University of Louvain
References
- Bourret, M.; Ratelle, C.F.; Plamondon, A. & Boisclair Châteauvert, G. (2023). Dynamics of parent-adolescent interactions during a discussion on career choice: The role of parental behaviors and emotions. Journal of Vocational Behavior, 141, https://doi.org/10.1016/j.jvb.2022.103837.
- Dupré, D. et al. (2020). A performance comparison of eight commercially available automatic classifiers for facial affect recognition. PLoS ONE, 15(4):e0231968. https://doi.org/10.1371/journal.pone.0231968.
- Krause, F.; Franke, N. (2023). Understanding Consumer Self-Design Abandonment: A Dynamic Perspective. Journal of Marketing. https://doi.org/10.1177/00222429231183977.
- Liu, S.; Wang, Y., Song, Y. (2023). Atypical facial mimicry for basic emotions in children with autism spectrum disorder. Autism Research, 16, 1375-1388.
- Malfait, A.; Puyvelde, M.; Detaille, F.; Neyt, X.; Waroquier, F. & Pattyn, N. (2023). Unveiling Readiness of Medical First Responders in Simulation Trainings: Insights beyond Queries. In: Jay Kalra (eds) Emerging Technologies in Healthcare and Medicine. AHFE International Conference. AHFE Open Access, vol 116. AHFE International, USA. http://doi.org/10.54941/ahfe1004375.
- Märtin, C., Bissinger B.C., & Asta, P. (2021). Optimizing the digital customer journey - Improving user experience by exploiting emotions, personas and situations for individualized user interface adaptations. Journal of Consumer Behavior, 1-12. https://doi.org/10.1002/cb.1964.
- Meng, Q. et al. (2020). On the effectiveness of facial expression recognition for evaluation of urban sound perception. Science of The Total Environment, 710, 135484, ISSN 0048-9697. https://doi.org/10.1016/j.scitotenv.2019.135484.
- Rogers, J. (2022). Ethnicity & FaceReader 9 - A FairFace Case Study. Volume 2 of the Proceedings of the joint 12th International Conference on Methods and Techniques in Behavioral Research and 6th Seminar on Behavioral Methods, held online, May 18-20, 2022. www.measuringbehavior.org. Editors: Andrew Spink, Jaroslaw Barski, Anne-Marie Brouwer, Gernot Riedel, & Annesha Sil (2022). https://doi.org/10.6084/m9.figshare.20066849. ISBN: 978-90-74821-94-0
- Stöckli, S. et al. (2018). Facial expression analysis with AFFDEX and FACET: A validation study. Behav Res Methods, 50(4), 1446-1460. https://doi.org/10.3758/s13428-017-0996-1.
- Talen, L. & den Uyl, T.E. (2021). Complex Website Tasks Increase the Expression Anger Measured with FaceReader Online. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2021.1938390.
- Yang, L.; Chen, X.; Guo, Q.; Zhang, J.; Luo, M.; Chen, Y.; Zou, X.; Xu, F. (2022). Changes in facial expressions in patients with Parkinson’s disease. Computer Speech & Language, 72(3), https://doi.org/10.1016/j.csl.2021.101286.
- Zaharieva, M.; Salvadori, E.; Messinger, D.; Visser, I.; Colonnesi, C. (2024). Automated facial expression measurement in a longitudinal sampleof 4‑ and 8‑month‑olds: Baby FaceReader 9 and manual coding of affective expressions. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02301-3.
Recent blog posts
The man in the maze: A behavioral science journey into consumer studies
As a researcher, one of my biggest thrills was being able to predict how someone was going to behave, especially without asking him or her.
Comparing machine emotion recognition with a human benchmark
Our emotions come across clear in our facial expressions. Due to this, facial expressions can be used in a wide variety of studies.