Injury Risk Prediction of Aerobics Athletes Based on Big Data and Computer Vision

In recent years, competitive aerobics has been rapidly popularized and developed, the level of sports skills also greatly improved. The performance some events gradually approached reached advanced level. Therefore, it is vital to invest in quantitative analysis cross-disciplinary comprehensive research related factors. This paper adopts big data technology computer vision based on convolutional neural network, according theories biomechanics image recognition, establish a loss risk prediction model for athletes. approach firstly used analyzing characteristics data. Secondly, combines network visually recognize images two-branch model. Finally, output can be fused accurately diagnose evaluate physical fitness development athletes, focus goal training content are clarified, scientific degree study help injury aerobic athletes applications vision.