ABSTRACT
Facial micro-expressions, as the name suggests, are very concise, unprompted facial expressions that appear either intentionally or unconsciously. These are challenging to detect, because they are of very short duration (<200 ms). It has become an interesting domain for analytical research in Machine Vision and the field of Psychology. Imitated micro-expressions are extremely hard to uncover. The aim of this research paper is to comprehensively review the existing micro-expression technological developments and compare the various data sets and give a recommended solution for future research. Challenges, such as limited data sets, overfitting, and data collection methods are discussed. We conclude by assessing the shortcomings of the existing models and suggesting possible solutions for advancing futuristic micro-expression research.
