Abstract
With the development of the times, teaching has not only stayed between people, but also gradually developed into the teaching interaction between man and machine. In the past, the teaching form was relatively single and old. Based on the intelligent visual sensor, this paper develops an auxiliary teaching system for the decomposition of aerobics action and reasonably uses the Internet and algorithms to catalog a series of aerobics action systems into the system. The DTW dynamic motion matching algorithm of the system will recognize human actions more accurately. The system will feed back human actions to the system in real time based on human feature recognition. Then, after comparison, the system will display the standard posture of this action and the aerobics posture in the next step. Therefore, this system develops teaching not only in class, but everywhere. The system not only improves the teaching quality of aerobics, but also strengthens the physical quality of teenagers. It has a new understanding of the standardization of aerobics teaching. After the function of the system is complete, the system will be distributed to aerobics learners. In many feedback information, the average use satisfaction has reached about 80%, which is a good performance index for the performance of the system itself.
Highlights
The physical health of students has gradually become the focus of public attention, and the concept of putting health first is thoroughly implemented
For face images with large illumination changes, reducing the number of iterations reduces the time complexity of face recognition, but it reduces the accuracy of the algorithm [7]. The design of this system is aimed at the shortcomings of actual aerobics teaching courseware and has developed functional modules including online courseware learning, online courseware arrangement, exchange forums, in-station message exchange, and content search
This paper develops an auxiliary teaching system for the decomposition of aerobics movements
Summary
The physical health of students has gradually become the focus of public attention, and the concept of putting health first is thoroughly implemented. The “health quality and standards” of students at all levels improves people’s living standards and raises health awareness, which is essential to promote the development of physical fitness testing systems. Both of these processes convert complex video data types into attributes in the form of arrays, vectors, and values containing motion data and use classifiers to identify and classify these attributes [8,9,10]. The current behavior methods can be divided into human body structure models, from the perspective of the structure and characteristics of motion, according to the human body model and behavior of motion
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