FaceReader uses an advanced 3D face modeling technique, with over 500 keypoints. The system is capable of modeling a face in realtime, without any manual initialization needed.
In addition to facial expressions, we develop and research state-of-the-art computer vision and machine learning concepts. Our related publications are found below:
 H. Emrah Tasli, Paul Ivan; “Turkish Presidential Elections TRT Publicity Speech Facial Expression Analysis”; arXiv:1408.3573
 Amogh Gudi, H. Emrah Tasli, Tim M. den Uyl, Andreas Maroulis; Deep Learning based FACS Action Unit Occurrence and Intensity Estimation, Int. Conf. on Automatic Face and Gesture Recognition, Facial Expression Recognition and Analysis Challenge FERA 2015.
 Tim M. den Uyl, H. Emrah Tasli, Paul Ivan, Mariska Snijdewind; Who do you want to be? Real-time Face Swap; Demo Paper at International Conference on Automatic Face and Gesture Recognition, FG2015.
 H. Emrah Tasli, Tim M. den Uyl, Hugo Boujut, Titus Zaharia; Real-Time Facial Character Animation; Demo Paper at International Conference on Automatic Face and Gesture Recognition, FG2015.
 Marten J. den Uyl, Hans van Kuilenburg. The FaceReader: Online facial expression recognition. Proceedings of Measuring Behaviour; 5th International Conference on Methods and Techniques in Behavioural Research.