The invention discloses a real-time video emotion
analysis method and
system based on
deep learning. The
analysis method comprises the following steps of S1, obtaining a training
data set; S2, recognizing microexpressions of the training
data set through an
algorithm based on a deep neural network, performing screening, and outputting 8 kinds of expression predicating values, wherein 8 kinds of expressions comprise a gentle expression, a happy expression, an amazed expression, a sad expression, an angry expression, a disgusted expression, a fear expression and a despised expression; S3, predicating shot human expressions through a
heart rate algorithm, and obtaining corresponding
heart rate values; and S4, comparing the
heart rate values obtained in the step S3 with the expression predicating values obtained in the step S2, and outputting the expressions the same as the heart rate values obtained in the step S3. According to the real-time video emotion
analysis method and
system basedon
deep learning disclosed by the invention, human face recognition in
machine vision and an image classification
algorithm are applied to detection of microexpressions and the heart rate, recognitionof the microexpressions is realized through the
deep learning algorithm, and the real-time video emotion analysis method and
system based on deep learning can be applied to the clinical field, the juridical field and the security field.