Ocean surface circulation based on video features and swimmer training monitoring

摘要

This paper aims at efficient recognition and video features and then studies the ocean surface circulation and swimmer training monitoring. Firstly, a method based on video feature extraction is proposed to describe the ocean surface circulation movement, and then a fusion method based on video dynamic and static features is designed for swimmer training monitoring, Finally, a video feature classification method based on dual stream improved C3d is designed to complete the recognition and classification. Then the characteristics of seasonal variation of tropical ocean surface circulation are analyzed, and the possible mode of seasonal water exchange between bay and ocean is discussed. Next, we analyze the temperature and salinity structure of the upper part of the ocean, the spatial distribution of the Arabian Sea and the Gulf, and the characteristics of seasonal variation. The expansion path and scope of the two water masses in the study area are clarified. Finally, the Bay Estuary 6° N segment, the net salt flux, and freshwater transport formula are used to quantitatively analyze the water exchange process of the tropical ocean surface circulation. Next, we will analyze the blood lactic acid level of the best Chinese swimmers, and note that Chinese swimmers are slightly insufficient in the case of high-intensity exercise. The lactic acid in the blood of the competition will be affected by the way of swimming, the gender of the athletes, and the venue of the competition. The purpose of training monitoring is to timely understand the athletes' body reaction to sports training, prevent excessive fatigue and sports injury, maximize sports performance in a short period of time, and achieve good results in the next ten games swimming competition. Based on the research of ocean surface circulation and swimmer training monitoring, this paper applies it to the video features, so as to improve the performance of swimmers.