About this Research Topic
As a Chinese saying goes, “Look at the weather when you step out; look at men’s faces when you step in.” Recognizing expressions is a very common activity in daily life. People can infer someone’s inner emotions from his or her facial expressions. However, not everyone writes their emotion on their face; someone may suppress true emotion and express a false facial expression depending on politeness, context, culture, or status. The suppressed expressions can be expressed fleetingly in the form of microexpressions, which usually last only 1/25 to 1/5 second.
Microexpressions were of importance for many practical applications because it reflects the true inner feeling, such as national security, deception detection, clinical therapy, emotion analysis, and human-computer interaction. The recognition of microexpressions is the premise of application of microexpression and now the recognition of microexpressions are getting more and more attention. However, perceiving other’s microexpressions is not easy. The context, culture, and perceiver himself affect the recognition of microexpression.
There are considerable efforts in the field of psychology, neuroscience, and computer science to recognize facial microexpressions. In this Research Topic, we welcome scientists from different fields and welcome papers which explore the microexpression recognition using behavioral indicators, eye movement, EEG, fNIRS, fMRI, and computer vision techniques. The work can be experimental or computational, and reviews are also welcome. The researchers should focus on how people perceive this kind of transit expression, what factors will influence the recognition, what the difference is between the recognizing microexpressions and macroexpressions (expressions with duration of longer time), what happened in the brain while recognizing microexpression, how to develop automatic recognition algorithms and models, and how the human recognition data can inform the computer automatic recognition.
While the scope is broad, authors are encouraged to clearly indicate how their studies address microexpression recognition.
Microexpressions were of importance for many practical applications because it reflects the true inner feeling, such as national security, deception detection, clinical therapy, emotion analysis, and human-computer interaction. The recognition of microexpressions is the premise of application of microexpression and now the recognition of microexpressions are getting more and more attention. However, perceiving other’s microexpressions is not easy. The context, culture, and perceiver himself affect the recognition of microexpression.
There are considerable efforts in the field of psychology, neuroscience, and computer science to recognize facial microexpressions. In this Research Topic, we welcome scientists from different fields and welcome papers which explore the microexpression recognition using behavioral indicators, eye movement, EEG, fNIRS, fMRI, and computer vision techniques. The work can be experimental or computational, and reviews are also welcome. The researchers should focus on how people perceive this kind of transit expression, what factors will influence the recognition, what the difference is between the recognizing microexpressions and macroexpressions (expressions with duration of longer time), what happened in the brain while recognizing microexpression, how to develop automatic recognition algorithms and models, and how the human recognition data can inform the computer automatic recognition.
While the scope is broad, authors are encouraged to clearly indicate how their studies address microexpression recognition.
Keywords: Macroexpression, Microexpression, Recognition, Computer Vision, Cognitive Neuroscience
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
