Calibrating a Non-isotropic Near Point Light Source Using a Plane

Jaesik Park, Sudipta N. Sinha, Y. Matsushita, Yu-Wing Tai, In-So Kweon
{"title":"Calibrating a Non-isotropic Near Point Light Source Using a Plane","authors":"Jaesik Park, Sudipta N. Sinha, Y. Matsushita, Yu-Wing Tai, In-So Kweon","doi":"10.1109/CVPR.2014.290","DOIUrl":null,"url":null,"abstract":"We show that a non-isotropic near point light source rigidly attached to a camera can be calibrated using multiple images of a weakly textured planar scene. We prove that if the radiant intensity distribution (RID) of a light source is radially symmetric with respect to its dominant direction, then the shading observed on a Lambertian scene plane is bilaterally symmetric with respect to a 2D line on the plane. The symmetry axis detected in an image provides a linear constraint for estimating the dominant light axis. The light position and RID parameters can then be estimated using a linear method. Specular highlights if available can also be used for light position estimation. We also extend our method to handle non-Lambertian reflectances which we model using a biquadratic BRDF. We have evaluated our method on synthetic data quantitavely. Our experiments on real scenes show that our method works well in practice and enables light calibration without the need of a specialized hardware.","PeriodicalId":319578,"journal":{"name":"2014 IEEE Conference on Computer Vision and Pattern Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.2014.290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31

Abstract

We show that a non-isotropic near point light source rigidly attached to a camera can be calibrated using multiple images of a weakly textured planar scene. We prove that if the radiant intensity distribution (RID) of a light source is radially symmetric with respect to its dominant direction, then the shading observed on a Lambertian scene plane is bilaterally symmetric with respect to a 2D line on the plane. The symmetry axis detected in an image provides a linear constraint for estimating the dominant light axis. The light position and RID parameters can then be estimated using a linear method. Specular highlights if available can also be used for light position estimation. We also extend our method to handle non-Lambertian reflectances which we model using a biquadratic BRDF. We have evaluated our method on synthetic data quantitavely. Our experiments on real scenes show that our method works well in practice and enables light calibration without the need of a specialized hardware.
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
用平面标定非各向同性近点光源
我们展示了一个非各向同性的近点光源,刚性地附着在相机上,可以使用弱纹理平面场景的多个图像进行校准。我们证明了如果光源的辐射强度分布(RID)相对于其主导方向是径向对称的,那么在朗伯场景平面上观察到的阴影相对于平面上的二维直线是双边对称的。在图像中检测到的对称轴为估计主光轴提供了线性约束。然后可以使用线性方法估计光源位置和RID参数。如果可用,镜面高光也可以用于光位置估计。我们还扩展了我们的方法来处理我们使用双二次BRDF建模的非朗伯反射率。我们用合成数据定量地评价了我们的方法。我们在真实场景中的实验表明,我们的方法在实践中效果良好,无需专门的硬件就可以实现光校准。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Enriching Visual Knowledge Bases via Object Discovery and Segmentation Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data Parsing Occluded People L0 Norm Based Dictionary Learning by Proximal Methods with Global Convergence Generalized Pupil-centric Imaging and Analytical Calibration for a Non-frontal Camera
×
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