Research And Implementation Of Facial Expression Recognition Algorithm Based On Machine Learning

In terms of interpersonal communication,in addition to natural language,physical movements,the facial expression is also a unique and important means of information transmission.Facial expressions are often able to convey a lot of language can not convey things.Especially for the disclosure of listed companies,if the facial expression of this feature can be used for computer interaction,it will greatly promote the solution of human-computer interaction.Facial expression recognition is to use machine and software to deal with facial expression information,extract its characteristics,and then through the identification of its characteristics of the process of classification.Its purpose is through the use of computer recognition facial expression of this intelligent human-computer interaction to achieve its psychological state of reasoning.In general,the facial expression recognition system consists of four parts:(1)expression image acquisition:in a picture with a facial expression to obtain an expression image;(2)expression image preprocessing:the expression of the image(3)facial feature extraction:for the pretreatment of the expression image,extract the characteristics of them;(4)expression classification recognition:the last step is to extract the facial features and The expression features inside the database are compared to classify the resulting emoticons.Face expression detection,analysis and identification is an important and challenging research topic in the field of computer and pattern recognition.Over the past few decades,there have been three steps in the process of facial facial expression analysis,namely image expression preprocessing,facial feature extraction and emotion classification.Facial facial expression research is mainly on people's facial performance and the corresponding emotional state of detection,interpretation and classification,and use the appropriate way to deal with these emotional information.Machine learning,as a new method of rapid development of pattern recognition,has a wide range of applications in facial recognition.In this paper,the neural network method is used to classify facial expressions for static face images.Firstly,the related work of facial expression recognition research is introduced,and the research status and related technology in this field are reviewed from the aspects of commonly used facial expression database,facial expression pretreatment,facial feature extraction and expression classification.With summary.The existing face expression classification is usually based on a specific expression database.The goal of this paper is to train the neural network classifier with the existing expression library and test with the executive image of the specific company so that the expression system can not only classify the images in the expression database accurately,but also have strong Robustness.