Yafei Sun

TL;DR: This paper presents the effort in creating an authentic facial expression database based on spontaneous emotions derived from the environment, and test and compare a wide range of classifiers from the machine learning literature that can be used for facial expression classification.

TL;DR: This work creates the first authentic facial expression database where the test subjects are showing the natural facial expressions based upon their emotional state and evaluates the several promising machine learning algorithms for emotion detection which include techniques such as Bayesian Networks, SVMs, and Decision trees.

TL;DR: This work introduces and test different Bayesian network classifiers for classifying expressions from video, and proposes an architecture of hidden Markov models (HMMs) for automatically segmenting and recognizing human facial expression from video sequences.

TL;DR: This work gives an overview of the current research toward automatic recognition of human emotions and shows the emotional or affective aspect of the communication to be at least if not more important than the functional aspect.