Institute of Physical Education, Huzhou University, Huzhou, Zhejiang 313000, China.
Jiaxing College Sports and Military Training Department, Jiaxing University, Jiaxing, Zhejiang 314000, China.
Comput Intell Neurosci. 2022 May 31;2022:9727415. doi: 10.1155/2022/9727415. eCollection 2022.
With the development of AI technology, human-computer interaction technology is no longer the traditional mouse and keyboard interaction. AI and VR have been widely used in early childhood education. In the process of the slow development and application of voice interaction, visual interaction, action interaction, and other technologies, multimodal interaction technology system has become a research hotspot. In this paper, dynamic image capture and recognition technology is integrated into early childhood physical education for intelligent interaction. According to the basic movement process and final node matching in children's sports training to judge children's physical behavior ability, attention is paid to identify the accuracy and safety of movement. The input images and questions are from the abstract clipart dataset of dynamic image recognition and the self-made 3D dataset of Web3D dynamic motion scene with the same style, which is similar to the action content in the actual preschool training teaching. Therefore, according to the idea of process capture and target recognition, on the basis of the original conditions of the recognition model, a new recognition model is developed through Zheng's target detector. The modified model is characterized by higher accuracy. Weapons need to combine process recognition and result recognition. The experimental results show that the improved model has the obvious advantages of high precision and fast speed, which provides a new research idea for the development of children's physical training simulation.
随着人工智能技术的发展，人机交互技术不再是传统的鼠标和键盘交互。人工智能和虚拟现实已经广泛应用于幼儿教育。在语音交互、视觉交互、动作交互等技术的缓慢发展和应用过程中，多模态交互技术系统已经成为研究热点。本文将动态图像采集识别技术融入到幼儿体育教育的智能互动中。根据儿童运动训练的基本动作过程和最终节点匹配来判断儿童的身体行为能力，注重识别动作的准确性和安全性。输入的图像和问题来自动态图像识别的抽象剪贴画数据集和具有相同风格的 Web3D 动态运动场景的自制 3D 数据集，与实际学前训练教学中的动作内容相似。因此，根据过程捕获和目标识别的思想，在识别模型的原始条件的基础上，通过郑的目标探测器开发了一个新的识别模型。改进后的模型的特点是具有更高的准确性。武器需要结合过程识别和结果识别。实验结果表明，改进后的模型具有高精度和快速的明显优势，为儿童体育训练模拟的发展提供了新的研究思路。
