So it is only applied to the frames identified by the spotting process described above. More specifically, it is not clear which facial features will result in the best recognition results for a certain AU, independently of the utilized classification scheme like Support Vector Machines, Decision Trees, or Neural Networks. The data should be first acquired and annotated in terms of activated AUs. References Publications referenced by this paper. Methods like edge detectors, Gabor wavelets, and texture-based deformable 3D models can prove suitable for realizing Transient Facial Feature Detectors. This paper has citations.
We developed various methods that can recognize a large number of AUs in either frontal or profile face image sequences.
Machine Analysis of Facial Expressions
Learning real-time object detectors: AI's Economic Impact This detector performs well only on images of expressionless faces. So it is only applied to the frames identified by the spotting process described above. Automating the analysis of facial expressions, would be highly beneficial for fields as diverse as security, behavioural science, medicine, communication, and education. Another 15 people watched the entire videos and had to spot each microexpression as well as identify it. Facial expressions play a significant role in our social and emotional lives.