Deep360Up:一种基于深度学习的VR图像垂直自动调整方法

Raehyuk Jung, Aiden Seung Joon Lee, Amirsaman Ashtari, J. Bazin
{"title":"Deep360Up:一种基于深度学习的VR图像垂直自动调整方法","authors":"Raehyuk Jung, Aiden Seung Joon Lee, Amirsaman Ashtari, J. Bazin","doi":"10.1109/VR.2019.8798326","DOIUrl":null,"url":null,"abstract":"Spherical VR cameras can capture high-quality immersive VR images with a 360° field of view. However, in practice, when the camera orientation is not straight, the acquired VR image appears tilted when displayed on a VR headset, which diminishes the quality of the VR experience. To overcome this problem, we present a deep learning-based approach that can automatically estimate the orientation of a VR image and return its upright version. In contrast to existing methods, our approach does not require the presence of lines or horizon in the image, and thus can be applied on a wide range of scenes. Extensive experiments and comparisons with state-of-the-art methods have successfully confirmed the validity of our approach.","PeriodicalId":315935,"journal":{"name":"2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Deep360Up: A Deep Learning-Based Approach for Automatic VR Image Upright Adjustment\",\"authors\":\"Raehyuk Jung, Aiden Seung Joon Lee, Amirsaman Ashtari, J. Bazin\",\"doi\":\"10.1109/VR.2019.8798326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spherical VR cameras can capture high-quality immersive VR images with a 360° field of view. However, in practice, when the camera orientation is not straight, the acquired VR image appears tilted when displayed on a VR headset, which diminishes the quality of the VR experience. To overcome this problem, we present a deep learning-based approach that can automatically estimate the orientation of a VR image and return its upright version. In contrast to existing methods, our approach does not require the presence of lines or horizon in the image, and thus can be applied on a wide range of scenes. Extensive experiments and comparisons with state-of-the-art methods have successfully confirmed the validity of our approach.\",\"PeriodicalId\":315935,\"journal\":{\"name\":\"2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VR.2019.8798326\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VR.2019.8798326","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

摘要

球形VR相机可以拍摄360°视野的高质量沉浸式VR图像。然而,在实际应用中,当摄像机的方向不垂直时,获取的VR图像在VR头显上显示时会出现倾斜,从而降低了VR体验的质量。为了克服这个问题,我们提出了一种基于深度学习的方法,可以自动估计VR图像的方向并返回其垂直版本。与现有的方法相比,我们的方法不需要在图像中存在线或地平线,因此可以应用于广泛的场景。广泛的实验和与最先进的方法的比较成功地证实了我们的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep360Up: A Deep Learning-Based Approach for Automatic VR Image Upright Adjustment
Spherical VR cameras can capture high-quality immersive VR images with a 360° field of view. However, in practice, when the camera orientation is not straight, the acquired VR image appears tilted when displayed on a VR headset, which diminishes the quality of the VR experience. To overcome this problem, we present a deep learning-based approach that can automatically estimate the orientation of a VR image and return its upright version. In contrast to existing methods, our approach does not require the presence of lines or horizon in the image, and thus can be applied on a wide range of scenes. Extensive experiments and comparisons with state-of-the-art methods have successfully confirmed the validity of our approach.
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
×
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:481959085
Book学术官方微信