Micro-expressions are short and subtle facial expressions, that we do not control with our nervous system. Among other things can occurrence of such micro-expressions indicate an attempt at hiding the real emotion. Algorithmic analysis of micro-expressions finds its value in the fields of public safety and clinical medicine. Research and development in micro-expression analysis focuses on algorithmic approaches, since it is borderline impossible for the naked eye to spot micro-expressions. In this work I do an overview of some deep learning methods for the classification of micro-expressions into one of the basic emotions (positive, negative, surprise, other) and report on their success at doing so, on various data sets.
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