Action unit detection is the task of detecting action units from a video - for example, types of facial action units lip tightening, cheek raising from a video of a face. CVPR Most of the existing work on automatic facial expression analysis focuses on discrete emotion recognition, or facial action unit detection. ECCV Facial action unit AU detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for AU detection. Browse state-of-the-art. You'll get the lates papers with code and state-of-the-art methods. Tip: you can also follow us on Twitter.
The FACS as we know it today was first published in , but was substantially updated in Using FACS, we are able to determine the displayed emotion of a participant. This analysis of facial expressions is one of very few techniques available for assessing emotions in real-time fEMG is another option. Other measures, such as interviews and psychometric tests, must be completed after a stimulus has been presented.
From the moment you are born, assuming normal eyesight, we open our eyes and fixate on the 43 muscles that control s of nuances of facial expressions and emotion intent in the face of our parents. They inform a reaction to how to interpret the world, an extended sensor to help learn the basic emotions and reactions to the world around us. In the Spring of a team of scientists and researchers at the Machine Perception Lab at University of California, San Diego, was forming the technology and the basic elements of what was to become Emotient. The founding team were widely regarded as spearheading the use of machine learning for facial expression analysis with over 20 years of experience pioneering machine learning and computer vision technology for facial behavior analysis. The team has published hundreds of peer reviewed scientific publications, starting in , which have been cited by thousands of other researchers in the field.