Facial expression analysis
FaceReader has been trained to classify expressions in one of the following categories:
These emotional categories have been described by Ekman  as the basic
or universal emotions. Additionally FaceReader can classify Valence a measure of the positive of negative attitude of your participants towards your content, and Arousal which indicates the level of excitement you content induces with your participants.
The FaceReader engine has been in development for about 20 years, improving recognition accuracy year over year.
Please visit the product description page at VicarVision or Noldus if you wish to read more about FaceReader.
Below you will find a description of the different steps of the algorithm.
All FaceReader Online processes run on the reliable
cloud solution for all of its processes. This approach of analysis in the cloud brings a number of advantages for our customers:
Rapid scaling of processing capabilities to deal with sudden bursts of demand. Even the recording data of thousands of participants can be analyzed within minutes.
High reliability and availability - Microsoft guarantees an uptime of over 99.9%.
Geo-redundancy - Servers are located in different geographical regions. This further improves the availability, and provides a better connectivity (ping/bandwidth) for users all over the world.
Maintainability - You always have the latest and best version of our software to work with.