Dynamic visualization simulation of light motion capture in dance image recognition based on IoT wearable devices

With the rapid development of the Internet of Things and smart wearable devices, there is an increasing demand for motion capture and image recognition technology. This study aims to develop an optical motion capture system based on wearable devices of the Internet of Things to achieve accurate recognition and dynamic visual simulation of dance movements. This paper uses a motion capture technique based on optical principle. First, multiple optical sensors were installed on the wearable device to capture the dancers' movements. Then through the image recognition algorithm, the image is processed and analyzed to extract the dancers' posture and movement information. Finally, through the simulation algorithm, the captured dancers' movements are transformed into dynamic visualizations in real time. The experimental results show that the system can accurately capture and identify the movements of different dancers and provide high-quality dynamic visualizations. Through the system, dancers can observe their movements in real time, check and improve dance skills, and improve the quality of dance performance.