Research on the Standing Long Jump Performance Evaluation System for Key Points of Human Skeletons

The standing long jump is a commonly employed measure for assessing the strength, velocity, and coordination of teenagers. It is crucial in conducting physical fitness evaluations in numerous countries. Nevertheless, the precision and cost-efficiency of conventional assessment techniques have posed challenges. Existing methods frequently lack accuracy and might be expensive, which restricts their wider use. This work presents a mirror vision algorithm specifically developed to enhance the assessment of standing long jumps by concentrating on crucial anatomical landmarks such as the human trunk, legs, and foot. Through the examination of these critical domains, the algorithm is capable of providing enhanced precision and reliability in performance evaluations. The main aim of this research is to tackle the limitations of conventional approaches, including the problems of imprecise assessments and exorbitant expenses. The study aims to provide a more dependable and cost-effective method for assessing the athletic performance of adolescents. This approach has the potential to improve the efficacy of physical fitness evaluations, rendering them more accessible and accurate, hence enabling the formulation of better-informed training and development plans for young athletes. In conclusion, this innovation has the potential to greatly enhance the methods used for worldwide physical education and sports assessments.