In this study, we explore the use of Extreme Learning Machine (ELM) for micro-expression recognition because of its fast learning ability and higher performance when compared with other models. Automatic recognition of micro-expressions using machine learning techniques thus promises a more effective result and saves time and resources. Micro-expressions are characterized by short duration and low intensity, hence, efforts to train humans in recognizing them have resulted in very low performances. With the rapid increase in security issues all over the world, the use of micro-expressions to understand one's state of mind has received major interest. Micro-expression recognition is a growing research area owing to its application in revealing subtle intention of humans, especially while under high stake conditions.
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