The invention discloses a human face
emotion recognition method in a mobile embedded complex environment. In the method, a human face is divided into main areas of a
forehead, eyebrows and eyes, cheeks, a
noise, a month and a chain, and 68 feature points are further divided. In view of the above feature points, in order to realize the human face
emotion recognition rate, the accuracy and the reliability in various environments, a human face and
expression feature classification method is used in a normal condition, a Faster R-CNN face area
convolution neural network-based method is used in conditions of light, reflection and shadow, a method of combining a Bayes Network, a Markoff chain and variational reasoning is used in complex conditions of motion,
jitter, shaking, and movement, and a method of combining a deep
convolution neural network, a super-resolution
generative adversarial network (SRGANs),
reinforcement learning, a
backpropagation algorithm and a dropout
algorithm is used in conditions of incomplete human face display, a multi-human face environment and noisy background. Thus, the human face expression recognition effects, the accuracy and the reliability can be promoted effectively.