With the development of Internet technology, Internet plus education has become a new mode of changing traditional education methods. Therefore, online physical education has attracted more and more attention. This paper introduces the sports object segmentation algorithm, designs an interactive multimedia online sports education platform by combining the research needs of sports online education platform, and analyzes online sports education from three aspects, sports teaching management, sports teaching resources, and sunshine sports activities, in order to improve the quality of sports education and improve students’ learning interest. Simulation results show that the algorithm is effective and can support the analysis of interactive multimedia online physical education platform.

We study the rehabilitation training of damaged parts of ice and snow sports clock and ensure the physical safety of athletes. The results show that the RBF neural network updates the center, weight, and width of the radial basis function, and the predicted maximum compliance is 99%, and the minimum compliance is 93%. After many analysis times, the prediction results show that the difference between the predicted degree of conformity and the actual results is less than 8%. The RBF neural network is trained according to the risk database of sports injury, and the RBF neural network will output corresponding values to realize sports injury estimation. The experimental results show that the designed model has high precision and efficiency.

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