DCC-net network model for motion data management based on infrared light sensor

In this paper, a network model named DCC-Net based on infrared image sensor is developed for sports data management. Optical imaging plays an important role in the collection and analysis of sports data, but the traditional methods have limitations in the aspects of illumination change and motion blur. To solve these problems, we propose a DCC-net network model based on infrared image sensor. The background of this study is to improve the efficiency of collection and management of sports data in order to promote the improvement of athletes' training and competitive performance. We use a combination of convolutional neural networks and recurrent neural networks to extract and understand motion information in infrared images. The experimental results show that the DCC-net network model has better performance than the traditional optical method in the aspects of illumination variation and motion blur, and provides more accurate and stable motion data. Therefore, DCC-net network model based on infrared image sensor is an effective sports data management tool, which can provide more comprehensive and accurate training and competitive support for athletes and coaches.