In order to solve the problem of observing the effect of rehabilitation physical training on basketball player injury, a kind of observation study on the effect of rehabilitation physical training on basketball player injury based on memory ultrasound examination was proposed. This study makes a comprehensive analysis of physical fitness training factors such as physical fitness test plan, training arrangement, training method, training monitoring, and effect evaluation. Through the experiment, it is found that there are still gaps in physical training, diagnostic standards, training plans and requirements, load monitoring, standardization of operation, nutrition, and recovery in the training organization. There are only 23.81% of full-time physical coaches and 25.40% of professional team doctors at all levels of sports teams. There were only 23.81% of full-time physical fitness coaches and 25.40% of professional team doctors in all levels of sports teams. Basketball players in the basketball injury survey had 67 sports injuries throughout the year, with a rate of 3.35 injuries per person and 2.48 injuries per 1000 hours. The location of chronic injuries is usually the lower back, knee joint, and ankle. The main injuries are due to the physical component, with injuries occurring most frequently throughout the training season in July, August, and September. Experiments show that good and professional physical training can reduce the risk of injury to a greater extent than strengthening the specific skills of athletes.

Behavior analysis plays a critical role in physical education. This paper resorts to computer vision technology to establish a classroom behavior analysis system for physical education. First, the behavior video is collected by a Kinect camera. Then, the behavior is recognized based on the symbiotic relationship and geometric constraints between human posture and interactive objects. The human skeleton is used to describe the behavior subject and the local area boundary boxes are divided with each node in the skeleton as the center. The human posture features are used to learn a structural classification model to recognize human behavior sequence. Finally, the behavior recognition results are used to analyze physical education. The experimental results show that the proposed behavior analysis framework can accurately recognize human behavior during physical education classes.