Realization of college sports multimedia teaching platform based on cloud computing motion image analysis

Abstract

Abstract In order to improve the ability of college sports multimedia teaching, dynamic image analysis and data management, a design scheme of college sports multimedia teaching platform based on cloud computing mode was proposed. The method of dynamic integrated allocation and fuzzy scheduling of multimedia teaching resources is adopted. The characteristic values and dynamic analysis of moving images of college sports multimedia teaching are extracted. By using hierarchical structure and image integration scheduling method, this paper analyzes the characteristic values of image analysis in college sports multimedia teaching and dynamic analysis of moving images. By using the methods of adaptive cooperative control and resource matching scheduling, the control objective allocation function of college sports multimedia teaching and dynamic analysis of moving images is constructed. The correlation of image information resources in college sports multimedia teaching is mined by using the ultra micro pixel feature matching method, and a big data mining and information fusion model for college sports multimedia education and dynamic analysis of motion images is constructed. Use cloud computing technology to provide users with various services, and use machine learning technology to analyze teaching data. Through priority scheduling and dynamic allocation methods, the dynamic allocation of teaching resources and dynamic analysis of moving images in the process of college sports multimedia teaching are realized. In ASP NET technology, cloud computing and Silverlight technology have realized the software development and design of college sports multimedia teaching platform under the motion image analysis mode. The simulation results show that using this method to design the college sports multimedia teaching platform under the motion image analysis mode can improve the dynamic distribution and mining ability of image information resources in college sports multimedia education. The platform has a high level of data fusion and a strong ability to analyze motion images.