אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

Facial expressions play a significant role in human communication and behavior.​ ​Psychologists have long studied the relationship between facial expressions and emotions.​ ​Paul Ekman et al., devised the Facial Action Coding System (FACS) to taxonomize human facial expressions and model their behavior.​ ​The ability to recognize facial expressions automatically, enables novel applications​ ​in fields like human-computer int​​eraction, social gaming, and psychological research.

There has been a tremendously active research in this field, with several recent papers​ ​utilizing convolutional neural networks (CNN) for feature extraction and inference.​ ​We employ CNN understanding methods to study the relation between the​ ​features these computational networks are using, the FACS and Action Units (AU).​ ​We apply these models to various tasks and tests using transfer learning,​ ​including cross-dataset validation, cross-task performance and micro-expression detection.