Daniel McDuff
ABSTRACT
We present a real-time facial expression recognition toolkit that can automatically code the expressions of multiple people simultaneously. The toolkit is available across major mobile and desktop platforms (Android, iOS, Windows). The system is trained on the world's largest dataset of facial expressions and has been optimized to operate on mobile devices and with very few false detections. The toolkit offers the potential for the design of novel interfaces that respond to users' emotional states based on their facial expressions. We present a demonstration application that provides real-time visualization of the expressions captured by the camera.
- Brave, S., and Nass, C. 2003. "Emotion in human- computer interaction." Human-Computer Interaction: 53. Google Scholar
Digital Library
- Dalal, N. and Triggs, B., 2005, June. Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on (Vol. 1, pp. 886--893). IEEE. Google ScholarDigital Library
- Ekman, P. and Friesen, W. 1978. "Facial Action Coding System: A technique for the measurement of facial movements." Consulting Psychologist.Google Scholar
- Friesen, W. and Ekman, P. 1983. "EMFACS-7: Emotional facial action coding system." Unpublished manuscript, University of California at San Francisco 2: 36.Google Scholar
- McDuff, D., Karlson, A., Kapoor, A., Roseway, A., and Czerwinski, M. 2012. "AffectAura: an intelligent system for emotional memory." In Proc of CHI '12. Google ScholarDigital Library
- McDuff, D., Kaliouby, R. and Picard, R. 2012. "Crowdsourcing facial responses to online videos." Affective Computing, IEEE Transactions on 3.4: 456--468. Google ScholarDigital Library
- Picard, R., Affective computing. MIT press, 2000.Google ScholarDigital Library
- Senechal, T., McDuff, D. and Kaliouby, R., 2015. "Facial Action Unit Detection Using Active Learning and an Efficient Non-Linear Kernel Approximation." In Proc. ICCV IEEE '15. Google ScholarDigital Library
- Ståhl, A., Höök, K., Svensson, M., Taylor, A., and Combetto, M. 2009. "Experiencing the affective diary." PERS UBIQUIT COMPUT, 13.5: 365--378. Google ScholarDigital Library
- Viola, P. and Jones, M. 2001. "Rapid object detection using a boosted cascade of simple features." PROC CVPR IEEE '01.Google Scholar
Index Terms
- AFFDEX SDK: A Cross-Platform Real-Time Multi-Face Expression Recognition Toolkit
Recommendations
Facial Expression Recognition in the Encrypted Domain Based on Local Fisher Discriminant Analysis
Facial expression recognition forms a critical capability desired by human-interacting systems that aim to be responsive to variations in the human's emotional state. Recent trends toward cloud computing and outsourcing has led to the requirement for ...
Determining facial expressions in real time
ICCV '95: Proceedings of the Fifth International Conference on Computer VisionWe suggest an approach to describing and tracking the deformation of facial features. We concentrate on the mouth since its shape is important in detecting emotion. However, we believe that our system could be extended to deal with other facial ...
The funcanny valley: a study of positive emotional reactions to strangeness
AcademicMindTrek '15: Proceedings of the 19th International Academic Mindtrek ConferenceThe uncanny valley hypothesis states that an artificial character creates an unsettling impression if it resembles a real human too closely. In previous literature, uncanniness has usually been interpreted as a single feature that manifests itself in ...
Comments