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In distance vocational education, teachers need to analyze according to the expression status of different students, so as to make corresponding training in training to improve training efficiency. At present, there are certain problems in the remote expression recognition of professional personnel. Based on this, this study analyzes the facial expression image and uses the wavelet transform algorithm to process the face image in complex lighting environment, thus improving the online transmission effect of the image. After that, this study uses orthogonal projection algorithm for face recognition. In addition, this paper enhances LBP features by dividing the original image into four images by wavelet decomposition. At the same time, in order to prevent the over-characteristics from reducing the classification accuracy and real-time calculation, this paper uses the PCA principal component analysis method to select the feature subset with the largest discrimination. Finally, through SVM, this article has done experiments on JAFFE facial expression database. The experimental results show that the proposed method has a significant improvement in the correct rate compared with the traditional LBP feature classification method and can improve the theoretical reference for subsequent related research.

RETRACTED ARTICLE: Research on professional talent training technology based on multimedia remote image analysis