Design and Application of Art Education Communication Platform Based on Machine Vision

Abstract

There are some problems in the design and application of the art education exchange platform. In order to further analyze the relevant content of the art education exchange, based on machine vision theory, model calibration, and coordinate change are adopted to modify the original model, so as to obtain the optimized model. This model can be used to analyze the design and application of art education platform. Relevant studies show that, according to the coordinate parameter curve, the parameter α plays a promoting role on the coordinate value, while the parameter β plays a promoting role on the coordinate value first and then plays an inhibiting role. The parameter γ also promotes and inhibits coordinate values. The curve corresponding to parameter M1 shows a gradual decline, and the curve of parameter M2 has little influence on coordinate data. The curve corresponding to parameter M3 also shows a linear trend of change. Through analysis, it can be seen that M3 has the greatest influence on coordinate data. By using machine vision model to design and analyze the communication platform of art education, the changing trend of different indicators can be obtained. It can be seen from the analysis that both language and vocal music have obvious stability in the calculation process, which is an inherent attribute of communication platform. Finally, the accuracy of the optimization model is verified by analyzing and predicting the data. This research can provide theoretical support for the application of machine vision model in other fields.