基于同心球建模的光场拼接

Siyao Zhou, Xin Jin, Pei Wang
{"title":"基于同心球建模的光场拼接","authors":"Siyao Zhou, Xin Jin, Pei Wang","doi":"10.1109/ICIP40778.2020.9190965","DOIUrl":null,"url":null,"abstract":"VR image in form of the spherical panoramic image is already widely available while enhancing its immersive experience with six degrees of freedom (6-DoF) is fundamentally required. Spherical panoramic light field (LF) becomes a potential solution because of recording the spatial and angular information of the light rays in the 360° spherical space. In this paper, a novel method is proposed to generate spherical panoramic LF by stitching LFs captured at different rotational angles. First, concentric spherical modeling is proposed to parameterize the recorded rays to eliminate the projection biases in registration. Then, the concentric spherical model-based LF registration which is insensitive to the ordering is introduced to transform each 4D LFs mesh accurately. Finally, the stitching result is projected to Two-parallel-plane (TPP) coordinates for viewing. Experimental results show that the proposed method outperforms the existing methods in terms of subjective quality and continuity in the stitched LF.","PeriodicalId":405734,"journal":{"name":"2020 IEEE International Conference on Image Processing (ICIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Light Field Stitching Based On Concentric Spherical Modeling\",\"authors\":\"Siyao Zhou, Xin Jin, Pei Wang\",\"doi\":\"10.1109/ICIP40778.2020.9190965\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"VR image in form of the spherical panoramic image is already widely available while enhancing its immersive experience with six degrees of freedom (6-DoF) is fundamentally required. Spherical panoramic light field (LF) becomes a potential solution because of recording the spatial and angular information of the light rays in the 360° spherical space. In this paper, a novel method is proposed to generate spherical panoramic LF by stitching LFs captured at different rotational angles. First, concentric spherical modeling is proposed to parameterize the recorded rays to eliminate the projection biases in registration. Then, the concentric spherical model-based LF registration which is insensitive to the ordering is introduced to transform each 4D LFs mesh accurately. Finally, the stitching result is projected to Two-parallel-plane (TPP) coordinates for viewing. Experimental results show that the proposed method outperforms the existing methods in terms of subjective quality and continuity in the stitched LF.\",\"PeriodicalId\":405734,\"journal\":{\"name\":\"2020 IEEE International Conference on Image Processing (ICIP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Image Processing (ICIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP40778.2020.9190965\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP40778.2020.9190965","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

球形全景图像形式的VR图像已经广泛应用,但增强其六自由度(6-DoF)的沉浸式体验是必不可少的。球形全景光场记录了光线在360°球形空间中的空间和角度信息,成为一种潜在的解决方案。本文提出了一种通过拼接不同旋转角度捕获的光场来生成球形全景光场的新方法。首先,采用同心球建模方法对记录的射线进行参数化,消除配准过程中的投影偏差;然后,引入了对序列不敏感的同心球面模型LF配准,实现了各4D LFs网格的精确变换;最后,将拼接结果投影到两平行平面(TPP)坐标系中供观看。实验结果表明,该方法在主观质量和拼接LF的连续性方面优于现有方法。
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
Light Field Stitching Based On Concentric Spherical Modeling
VR image in form of the spherical panoramic image is already widely available while enhancing its immersive experience with six degrees of freedom (6-DoF) is fundamentally required. Spherical panoramic light field (LF) becomes a potential solution because of recording the spatial and angular information of the light rays in the 360° spherical space. In this paper, a novel method is proposed to generate spherical panoramic LF by stitching LFs captured at different rotational angles. First, concentric spherical modeling is proposed to parameterize the recorded rays to eliminate the projection biases in registration. Then, the concentric spherical model-based LF registration which is insensitive to the ordering is introduced to transform each 4D LFs mesh accurately. Finally, the stitching result is projected to Two-parallel-plane (TPP) coordinates for viewing. Experimental results show that the proposed method outperforms the existing methods in terms of subjective quality and continuity in the stitched LF.
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
Deep Adversarial Active Learning With Model Uncertainty For Image Classification Emotion Transformation Feature: Novel Feature For Deception Detection In Videos Object Segmentation In Electrical Impedance Tomography For Tactile Sensing A Syndrome-Based Autoencoder For Point Cloud Geometry Compression A Comparison Of Compressed Sensing And Dnn Based Reconstruction For Ghost Motion Imaging
×
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