Research on the application of fusion of image recognition technology and sentiment analysis algorithms for psychological intervention

Mental health issues have become a global concern.Aiming at the complexity of individual facial emotion expression in the task of analyzing mental health status, this study proposes a face emotion recognition method oriented to psychological intervention.The method integrates image recognition and sentiment analysis techniques, adopts Adaboost algorithm for face detection, generates an emotion region suggestion network based on face image recognition, and constructs an image sentiment classification network through feature map mapping and shared convolution.The method is then applied to the mental health recognition system.The model in this paper avoids the effects of individual and illumination differences.It has good face emotion recognition on several datasets, and the prediction accuracies are above 90%, especially for Happy emotion.In the comparison with other recognition methods, the recognition accuracy of this paper's model is improved by 12.92% to 22.95%.The experiments show that the proposed face emotion recognition method can effectively predict the emotion of facial expression data in the mental health recognition system, and promote the assessment of individual mental health status and emotion management.