School of New Media Art, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China.
School of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
Comput Intell Neurosci. 2022 Jun 2;2022:1168012. doi: 10.1155/2022/1168012. eCollection 2022.
The construction of 3D design model is a hotspot of applied research in the fields of clothing functional design system teaching and display. The simple 3D clothing visualization postprocessing lacks interactive functions, which is a hot issue that needs to be solved urgently at present. Based on analyzing the existing clothing modeling technology, template technology, and fusion technology, and based on the multimodal clustering network theory, this paper proposes a 3D clothing design resource knowledge graph modeling method with multiple fusion of features and templates. The position of each joint point is converted into the coordinate system centered on the torso point in advance and normalized to avoid the problem that the relative position of the camera and the collector cannot be determined, and the shape of different collectors is different. The paper provides a multimodal clustering network intelligence method, illustrates the interoperability of users switching between different design networks in the seamless connection movement, and combines the hybrid intelligence algorithm with the fuzzy logic interpretation algorithm to solve the problems in the field of 3D clothing design service quality. During the simulation process, the research scheme builds a logical multimodal clustering network framework, which integrates compatibility access and global access partition fusion of style templates to achieve information extraction of clothing parts. The experimental results show that the realistic 3D clothing modeling can be achieved by layering the 3D clothing map, contour features, clothing size features, and color texture features with the modeling template. The developed ActiveX control is mounted on MSN, and the system is compatible. The performance and integration rate reached 77.1% and 89.7%, respectively, which effectively strengthened the practical role of the 3D clothing design system.
三维设计模型的构建是服装功能设计系统教学和展示领域应用研究的热点。简单的三维服装可视化后处理缺乏交互功能，是当前急需解决的热点问题。本文在分析现有服装建模技术、模板技术和融合技术的基础上，基于多模态聚类网络理论，提出了一种基于多模态聚类网络理论的多特征和模板融合的三维服装设计资源知识图建模方法。首先将每个关节点的位置转换到以躯干点为中心的坐标系中，并进行归一化处理，以避免相机和采集器的相对位置无法确定以及不同采集器形状不同的问题。本文提出了一种多模态聚类网络智能方法，说明了用户在不同设计网络之间切换时的互操作性，结合混合智能算法和模糊逻辑解释算法，解决了三维服装设计服务质量领域的问题。在模拟过程中，研究方案构建了一个逻辑多模态聚类网络框架，集成了风格模板的兼容性访问和全局访问分区融合，实现了服装部件的信息提取。实验结果表明，通过分层 3D 服装图、轮廓特征、服装尺寸特征和颜色纹理特征与建模模板，可以实现真实的 3D 服装造型。开发的 ActiveX 控件安装在 MSN 上，系统具有兼容性。性能和集成率分别达到 77.1%和 89.7%，有效增强了三维服装设计系统的实用性。
