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 ( P = 0.021 < 0.05 ). 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.
Highlights
Physical education can effectively enhance students’ physique, cultivate their sports skills, and improve their health
A discriminant model with hidden variables is established to detect complex action and atomic action, and the mapping matrix is used to reflect the many to one relationship between video segment and atomic action, so as to realize the goal of accurately identifying complex action in video segment and reduce the difficulty of students’ video learning [4]
Lyu et al plan to capture the urban scene from the angle of inclined UAV and propose a new high-resolution UAV semantic segmentation data set UAVid data set, which is composed of 30 video sequences
Summary
Physical education can effectively enhance students’ physique, cultivate their sports skills, and improve their health. Ma and Song proposed a moving object detection method in H.264/AVC compressed domain for video surveillance applications, which uses H.264 to compress the information in the bit stream, while reducing the computational complexity and memory requirements, and completes the detection and segmentation of moving objects through motion vectors and quantization parameters [15] It can be seen from the above research results that there are a lot of researches on dynamic video segmentation, human behavior recognition in video, video monitoring, and other different directions in the current society, but the research on big data dynamic programming algorithm for segmentation, recognition, and annotation of sports teaching video or professional athletes’ skill display video is limited. The importance of video action recognition technology based on big data dynamic programming algorithm in traditional sports teaching in colleges and universities will be discussed. This study has a certain reference value for promoting the current physical education reform policy
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