Approximate svBRDF Estimation From Mobile Phone Video

Rachel A. Albert, D. Chan, Dan B. Goldman, J. F. O'Brien
{"title":"Approximate svBRDF Estimation From Mobile Phone Video","authors":"Rachel A. Albert, D. Chan, Dan B. Goldman, J. F. O'Brien","doi":"10.2312/SRE.20181168","DOIUrl":null,"url":null,"abstract":"We describe a new technique for obtaining a spatially varying BRDF (svBRDF) of a flat object using printed fiducial markers and a cell phone capable of continuous flash video. Our homography-based video frame alignment method does not require the fiducial markers to be visible in every frame, thereby enabling us to capture larger areas at a closer distance and higher resolution than in previous work. Pixels in the resulting panorama are fit with a BRDF based on a recursive subdivision algorithm, utilizing all the light and view positions obtained from the video. We show the versatility of our method by capturing a variety of materials with both one and two camera input streams and rendering our results on 3D objects under complex illumination.","PeriodicalId":363391,"journal":{"name":"Eurographics Symposium on Rendering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurographics Symposium on Rendering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/SRE.20181168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

We describe a new technique for obtaining a spatially varying BRDF (svBRDF) of a flat object using printed fiducial markers and a cell phone capable of continuous flash video. Our homography-based video frame alignment method does not require the fiducial markers to be visible in every frame, thereby enabling us to capture larger areas at a closer distance and higher resolution than in previous work. Pixels in the resulting panorama are fit with a BRDF based on a recursive subdivision algorithm, utilizing all the light and view positions obtained from the video. We show the versatility of our method by capturing a variety of materials with both one and two camera input streams and rendering our results on 3D objects under complex illumination.
从手机视频中估计svBRDF
我们描述了一种使用打印基准标记和能够连续闪光视频的手机获得平面物体的空间变化BRDF (svBRDF)的新技术。我们基于同形图的视频帧对齐方法不需要在每一帧中都能看到基准标记,从而使我们能够以更近的距离和更高的分辨率捕获更大的区域。基于递归细分算法,利用从视频中获得的所有光线和视图位置,将所得全景图中的像素与BRDF进行拟合。我们通过捕获一个和两个相机输入流的各种材料并在复杂照明下渲染我们在3D对象上的结果来展示我们方法的多功能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信