通过混合现实增强零售行业的客户体验

Yirui Jiang, T. Tran, Leon Williams, Jaime Palmer, Edgar Simson, Daniel Benson, Michael Christopher, Daila Christopher
{"title":"通过混合现实增强零售行业的客户体验","authors":"Yirui Jiang, T. Tran, Leon Williams, Jaime Palmer, Edgar Simson, Daniel Benson, Michael Christopher, Daila Christopher","doi":"10.1145/3480433.3480438","DOIUrl":null,"url":null,"abstract":"∗Nowadays, customization by mixed reality to enhance the customer experience plays an important role in the retail industry. Customers can choose and customize products with their images and labels in a virtual reality environment. However, the existing asset creation pipelines are labor-intensive and time-consuming to display the images and labels (aka logos) on 3D product models, and cannot be easily customized by customers in real-time. In this paper, we thus propose a real-time 3D logo mapping framework for converting 3D logo mesh from a specified image and fitting it to the 3D product models. In the framework, Convolutional Neural Network (CNN) is adopted to reconstruct 3D logo/product models from their images. The detailed 3D information and the logo location provided by a customer are used to select the effective sampling points to mesh deformation. This method can preserve both the visual quality and details of 3D product models. Experimental results, carried out on various sizes of logos and types of products, show that our method can produce accurately and quickly customized logos on 3D product models.","PeriodicalId":415865,"journal":{"name":"2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Enhancing the Customer Experience by Mixed Reality in the Retail Industry\",\"authors\":\"Yirui Jiang, T. Tran, Leon Williams, Jaime Palmer, Edgar Simson, Daniel Benson, Michael Christopher, Daila Christopher\",\"doi\":\"10.1145/3480433.3480438\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"∗Nowadays, customization by mixed reality to enhance the customer experience plays an important role in the retail industry. Customers can choose and customize products with their images and labels in a virtual reality environment. However, the existing asset creation pipelines are labor-intensive and time-consuming to display the images and labels (aka logos) on 3D product models, and cannot be easily customized by customers in real-time. In this paper, we thus propose a real-time 3D logo mapping framework for converting 3D logo mesh from a specified image and fitting it to the 3D product models. In the framework, Convolutional Neural Network (CNN) is adopted to reconstruct 3D logo/product models from their images. The detailed 3D information and the logo location provided by a customer are used to select the effective sampling points to mesh deformation. This method can preserve both the visual quality and details of 3D product models. Experimental results, carried out on various sizes of logos and types of products, show that our method can produce accurately and quickly customized logos on 3D product models.\",\"PeriodicalId\":415865,\"journal\":{\"name\":\"2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3480433.3480438\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3480433.3480438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

如今,混合现实定制技术在零售行业中扮演着重要的角色。客户可以在虚拟现实环境中选择和定制带有自己的图像和标签的产品。然而,现有的资产创建管道在3D产品模型上显示图像和标签(又名徽标)是劳动密集型和耗时的,并且不容易由客户实时定制。因此,在本文中,我们提出了一个实时3D标识映射框架,用于从指定图像转换3D标识网格并将其拟合到3D产品模型中。在该框架中,采用卷积神经网络(CNN)从logo/产品的图像中重建3D logo/产品模型。利用客户提供的详细三维信息和标识位置,选择网格变形的有效采样点。该方法既能保持产品三维模型的视觉质量,又能保留产品三维模型的细节。在不同尺寸、不同类型的产品上进行的实验结果表明,我们的方法可以准确、快速地在3D产品模型上生成定制的logo。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Enhancing the Customer Experience by Mixed Reality in the Retail Industry
∗Nowadays, customization by mixed reality to enhance the customer experience plays an important role in the retail industry. Customers can choose and customize products with their images and labels in a virtual reality environment. However, the existing asset creation pipelines are labor-intensive and time-consuming to display the images and labels (aka logos) on 3D product models, and cannot be easily customized by customers in real-time. In this paper, we thus propose a real-time 3D logo mapping framework for converting 3D logo mesh from a specified image and fitting it to the 3D product models. In the framework, Convolutional Neural Network (CNN) is adopted to reconstruct 3D logo/product models from their images. The detailed 3D information and the logo location provided by a customer are used to select the effective sampling points to mesh deformation. This method can preserve both the visual quality and details of 3D product models. Experimental results, carried out on various sizes of logos and types of products, show that our method can produce accurately and quickly customized logos on 3D product models.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Enhanced Cognitive Training using Virtual Reality: Examining a Memory Task Modified for Use in Virtual Environments A Sport Project and Its Future Applications: How to Implement Speculative Design to Fulfill Users’ Needs Virtual Reality Oriented Modeling and Simulation of Amphibious Aircraft Forest Fire Extinguishing Mission Scene Design and Implementation of “Winning Luding Bridge” Immersion FPS Game Based on Unity3D Technology Point Cloud Interaction and Manipulation in Virtual Reality
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1