With the continuous deepening of economic globalization and the continuous development of Internet big data, the spread of martial arts culture has attracted people’s attention. The advent of the Internet big data era has brought new opportunities and media for the dissemination of martial arts culture but also brought certain risks and challenges. This paper firstly uses the literature method, logical analysis method, and related theories of communication, with the help of the SWOT strategic analysis method, to analyze the internal advantages and disadvantages faced by martial arts culture communication itself, as well as the external opportunities in the context of the Internet big data era and challenges. In order to realize the target detection and tracking task of Martial athletes, this paper proposes a target detection and tracking algorithm for Martial athletes. First, the algorithm constructs and trains a fully CNN-based athlete target detection model, which can detect the first frame of athlete targets in martial arts competitions or martial arts training videos. Experiments show that the athlete positioning information output by the detection model and the video frame sequence are jointly input into the athlete target tracking module based on neighborhood similarity, so as to realize the target tracking of martial arts athletes.
In the process of the development of sports resources, the first step is to strengthen mechanism construction, including the government and the market “- poor areas” tripartite coordination mechanism, the development of sports resource development policy supervision mechanism, sports resource development precision poverty alleviation mechanism, legal protection mechanism, and accountability mechanism. The establishment of the fitness model recommendation model is realized. The fitness pattern recommendation model itself is a multibranch decision tree model. Therefore, as long as it is a variety of fitness methods, according to different classification, in the fitness database to add the corresponding classification, this is helpful to build a multibranch decision tree model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.