Real-time micro-expression detection from high speed cameras
Diana Laura Borza, Răzvan Bogdan ITU, Radu Gabriel Danescu · 2017
This work presents an original real time, robust micro-expression detection algorithm. The algorithm analyses the movement modifications that occur around the most prominent facial regions using two absolute frame differences. Next, a machine learning algorithm is used to predict if a micro-expression occurred at a given frame t. Two classifiers were evaluated: decision tree and random forest classifier. The robustness of the proposed solution is increased by further processing the preliminary predictions of the classifier: the appropriate predicted micro-expression intervals are merged together and the interval that are too short are filtered out. The proposed solution achieved an 86.95% true positive rate on CASME2 dataset. The mean execution time of the proposed solution on 640×480 images is 9 milliseconds.