Fitness training driven by image target detection technology

Abstract

The fitness training system needs to capture the training staff dynamics in real time, but it is difficult to capture the training staff dynamics during the actual training process. Based on this, this study uses the physical characteristics of fitness trainers as indicators for image target detection. According to the human body will dissipate more heat during the fitness process, this study uses infrared capture as the basis of image capture detection technology, uses FCM clustering algorithm as the fuzzy image background segmentation algorithm, and uses k-means clustering analysis to study the gray histogram and propose a composite classification feature tracking method for trainer image tracking. Combined with the experimental research, the research shows that the research method utilizes the advantages of the composite classification feature to improve the detection rate of the human target. Therefore, it is a real-time and very effective infrared image human detection algorithm.