In order to solve the problem of sports medical image in basketball training, a sports medical image modeling research method based on injury prevention in basketball training was proposed. By the method, the current situation of sports injury in university basketball was investigated. At the same time, the injury factors were analyzed on four occasions, including basketball class, extracurricular activities, competition, and training. In order to reduce the occurrence of injury and enhance the security of basketball sports for nonbasketball students of physical education, combined with the problems and reasons, the corresponding suggestions were put forward. Through the experiment, it was found that the incidence of basketball injury for nonbasketball male university students was as high as 90.7%. The results of the experiment showed that it was necessary to enhance the awareness of self-protection, control emotions and exhibitionism, strengthen physical training, attach importance to basic skills training, do warm-up activities, stay focused, pay attention to exercise load, and prevent excessive fatigue.
In order to generate 3D virtual human animation with smoother actions and richer and more vivid expressions, this article proposes a system based on dual cameras to synchronously capture human facial expressions and human posture, so as to better generate 3D virtual human animation. Firstly, the 2D features of the image are extracted through facial expression, and the benchmark is provided for the standard 3D coordinate values. At the same time, the 3D pose fusion is realized by using the pose measurement algorithm for human motion capture. Through the test, it is found that the two fusion algorithms can meet the requirements of the static accuracy of 0.5° and the dynamic accuracy of 0°, and the three-dimensional model of a virtual human body has a good effect in data-driven animation. The experiments show that the system can better capture facial expressions and human posture synchronously, and the frame rate in the experimental test can reach 20 fps, which can generate more natural and realistic 3D virtual human animation in real time.
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