基于虚拟现实技术的服装试穿三维成像模型构建探索

Jingyuan Ren, Xiaoyan Hu
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引用次数: 0

摘要

随着虚拟现实技术(VRt)的不断发展,服装行业开始利用 VRt 建立三维服装试穿模型,为消费者提供全方位的试穿效果。然而,传统的服装 3D (三维)成像模型构建方法存在一定的缺陷。例如,试衣模型的构建是一个从平面到立体的过程,而三维试衣模型则是一个从二维到三维的过程,这使得用户在试衣过程中无法获得更加直观、形象、全面的试衣效果。本文在总结现有服装三维成像模型构建方法的基础上,提出了一种基于 VRt 的服装三维试衣模型构建方法,并将其应用于实际服装试衣中。这为消费者提供了一种全面的服装试穿方法,从而提高了消费者在购买服装时的购物效率和质量。研究结果表明,使用 VRt 系统获得积极评价的比例为 92%,而使用传统技术系统获得积极评价的比例仅为 10%,这表明 VRt 与构建服装试穿三维成像模型之间存在正相关关系。基于 VRt 的服装试穿系统具有很强的实用意义,但目前仍处于初步探索阶段。本文提出的系统不包括人脸建模功能。因此,今后可以考虑增加人脸重建模块,通过照片重建等方式建立更加个性化的人体模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploration on 3D imaging model construction of clothing fitting based on virtual reality technology

With the continuous development of virtual reality technology (VRt), the clothing industry has begun to use VRt to build three-dimensional clothing fitting models, which provide consumers with a comprehensive range of fitting effects. However, the traditional 3D (three-dimensional) imaging model construction method for clothing has certain shortcomings. For example, the construction of fitting models is a process from planar to three-dimensional, while the three-dimensional fitting model is a process from two-dimensional to three-dimensional, which makes it impossible for users to obtain a more intuitive, visual, and comprehensive fitting effect during fitting. On the basis of summarizing the existing methods for building 3D imaging models of clothing, this paper proposed a method for building 3D clothing fitting models based on VRt and applied it to actual clothing fitting. This provided consumers with a comprehensive method for fitting clothing, thereby improving the shopping efficiency and quality of consumers when purchasing clothing. The research results show that the proportion of positive evaluations using VRt systems was 92%, while the proportion of positive evaluations using conventional technology systems was only 10%, indicating a positive relationship between VRt and the construction of 3D imaging models for clothing fitting. The VRt-based clothing fitting system has strong practical significance, but it is still in the preliminary exploration stage. The system proposed in this paper does not include face modeling function. Therefore, in the future, we can consider adding a face reconstruction module to build a more personalized human model through photo reconstruction and other ways.

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