非视距成像中首回光子的几何形状

Chia-Yin Tsai, Kiriakos N. Kutulakos, S. Narasimhan, Aswin C. Sankaranarayanan
{"title":"非视距成像中首回光子的几何形状","authors":"Chia-Yin Tsai, Kiriakos N. Kutulakos, S. Narasimhan, Aswin C. Sankaranarayanan","doi":"10.1109/CVPR.2017.251","DOIUrl":null,"url":null,"abstract":"Non-line-of-sight (NLOS) imaging utilizes the full 5D light transient measurements to reconstruct scenes beyond the cameras field of view. Mathematically, this requires solving an elliptical tomography problem that unmixes the shape and albedo from spatially-multiplexed measurements of the NLOS scene. In this paper, we propose a new approach for NLOS imaging by studying the properties of first-returning photons from three-bounce light paths. We show that the times of flight of first-returning photons are dependent only on the geometry of the NLOS scene and each observation is almost always generated from a single NLOS scene point. Exploiting these properties, we derive a space carving algorithm for NLOS scenes. In addition, by assuming local planarity, we derive an algorithm to localize NLOS scene points in 3D and estimate their surface normals. Our methods do not require either the full transient measurements or solving the hard elliptical tomography problem. We demonstrate the effectiveness of our methods through simulations as well as real data captured from a SPAD sensor.","PeriodicalId":6631,"journal":{"name":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","volume":"74 1","pages":"2336-2344"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"77","resultStr":"{\"title\":\"The Geometry of First-Returning Photons for Non-Line-of-Sight Imaging\",\"authors\":\"Chia-Yin Tsai, Kiriakos N. Kutulakos, S. Narasimhan, Aswin C. Sankaranarayanan\",\"doi\":\"10.1109/CVPR.2017.251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Non-line-of-sight (NLOS) imaging utilizes the full 5D light transient measurements to reconstruct scenes beyond the cameras field of view. Mathematically, this requires solving an elliptical tomography problem that unmixes the shape and albedo from spatially-multiplexed measurements of the NLOS scene. In this paper, we propose a new approach for NLOS imaging by studying the properties of first-returning photons from three-bounce light paths. We show that the times of flight of first-returning photons are dependent only on the geometry of the NLOS scene and each observation is almost always generated from a single NLOS scene point. Exploiting these properties, we derive a space carving algorithm for NLOS scenes. In addition, by assuming local planarity, we derive an algorithm to localize NLOS scene points in 3D and estimate their surface normals. Our methods do not require either the full transient measurements or solving the hard elliptical tomography problem. We demonstrate the effectiveness of our methods through simulations as well as real data captured from a SPAD sensor.\",\"PeriodicalId\":6631,\"journal\":{\"name\":\"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)\",\"volume\":\"74 1\",\"pages\":\"2336-2344\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"77\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.2017.251\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.2017.251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 77

摘要

非视距成像(NLOS)利用全5D光瞬态测量来重建相机视野之外的场景。在数学上,这需要解决椭圆层析成像问题,从NLOS场景的空间复用测量中分离出形状和反照率。在本文中,我们提出了一种新的NLOS成像方法,通过研究三反射光路的第一返回光子的性质。我们表明,首次返回光子的飞行时间仅取决于NLOS场景的几何形状,并且每次观测几乎总是从单个NLOS场景点生成。利用这些特性,我们推导了一种NLOS场景的空间雕刻算法。此外,通过假设局部平面性,我们推导了一种算法来定位NLOS场景中的三维点并估计它们的表面法线。我们的方法既不需要完整的瞬态测量,也不需要解决硬椭圆层析成像问题。我们通过模拟以及从SPAD传感器捕获的真实数据证明了我们方法的有效性。
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
The Geometry of First-Returning Photons for Non-Line-of-Sight Imaging
Non-line-of-sight (NLOS) imaging utilizes the full 5D light transient measurements to reconstruct scenes beyond the cameras field of view. Mathematically, this requires solving an elliptical tomography problem that unmixes the shape and albedo from spatially-multiplexed measurements of the NLOS scene. In this paper, we propose a new approach for NLOS imaging by studying the properties of first-returning photons from three-bounce light paths. We show that the times of flight of first-returning photons are dependent only on the geometry of the NLOS scene and each observation is almost always generated from a single NLOS scene point. Exploiting these properties, we derive a space carving algorithm for NLOS scenes. In addition, by assuming local planarity, we derive an algorithm to localize NLOS scene points in 3D and estimate their surface normals. Our methods do not require either the full transient measurements or solving the hard elliptical tomography problem. We demonstrate the effectiveness of our methods through simulations as well as real data captured from a SPAD sensor.
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
FFTLasso: Large-Scale LASSO in the Fourier Domain Semantically Coherent Co-Segmentation and Reconstruction of Dynamic Scenes Coarse-to-Fine Segmentation with Shape-Tailored Continuum Scale Spaces Joint Gap Detection and Inpainting of Line Drawings Wetness and Color from a Single Multispectral Image
×
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