Affiliation:
1. Jilin University, Changchun, Jilin 130012, China
Abstract
Physical education teaching is conducive to the cultivation of students’ lifelong sports consciousness, which can improve students’ health and enhance their physique. In order to explore the importance of traditional sports based on big data dynamic programming algorithm into college physical education, the video action recognition and segmentation technology based on big data dynamic programming algorithm is designed. The complex actions in traditional sports teaching video are divided into a series of atomic actions with single semantics. The human action results are modeled according to the relationship between complex actions and atomic actions, and the actions are completed, and the changes of students’ sports level were compared under different teaching modes. Compared with the no segment method, the average accuracy of the experimental design method increased by 2.80% and 3.50%, respectively, and the action recognition rate increased by 11.50%, 8.40%, 13.60%, 13.50%, and 13.60%, respectively. Before and after the experiment, there was a significant difference in the performance of the experimental group (
). The results show that the traditional sports teaching mode based on video action recognition technology of big data dynamic programming algorithm can effectively improve the teaching quality of sports teaching. This research has a certain reference value to promote the current physical education teaching reform policy.
Funder
Research on the Construction of College Students’ Sports and Health Evaluation System, China
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Cited by
5 articles.
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