Fast Region based Convolutional Neural Network for Emotion Recognition in Health Care Applications
Stress in human is one of the major concerns for our general population, because it is the cause for certain medical problems and enormous corporate financial misfortunes. Consistent high mental tasks and tireless occasions, leads to continuous change and need for adaption, make the issue ever more difficult for human. This research work collects facial images from video frames and the recognizer for face expression separates the images retrieved. The model of data training uses the Fast Region based Convolutional Neural network to train data and the recognizer also uses the Fast RCNN to track the emotional state of a data. Our performance analysis shows that the proposed scheme is having 92% accuracy in recognizing stress related facial expressions.