Scene-aware Foveated Rendering

Runze Fan;Xuehuai Shi;Kangyu Wang;Qixiang Ma;Lili Wang
{"title":"Scene-aware Foveated Rendering","authors":"Runze Fan;Xuehuai Shi;Kangyu Wang;Qixiang Ma;Lili Wang","doi":"10.1109/TVCG.2024.3456157","DOIUrl":null,"url":null,"abstract":"We propose a new scene-aware foveated rendering method, which incorporates the scene awareness and characteristics of the human visual system into the mapping-based foveated rendering framework. First, we generate the conservative visual importance map that encodes the visual features of the scene, visual acuity, and gaze motion. Second, we construct the pixel size control map using a convolution kernel method. Third, we utilize the pixel size control map to guide the foveated rendering. At last, a temporal coherent refinement strategy is used to maintain the smooth foveated rendering for the adjacent frames. Compared to the state-of-the-art mapping-based foveated rendering methods using the same compression ratio, our method achieves smaller MSE, higher PSNR, and SSIM in the fovea, periphery, salient regions, and the whole image. We also conducted user studies, and the results proved that the perceptual quality of our method has a high visual similarity with the around truth rendered with the full resolution.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"30 11","pages":"7097-7106"},"PeriodicalIF":6.5000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE transactions on visualization and computer graphics","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10675380/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We propose a new scene-aware foveated rendering method, which incorporates the scene awareness and characteristics of the human visual system into the mapping-based foveated rendering framework. First, we generate the conservative visual importance map that encodes the visual features of the scene, visual acuity, and gaze motion. Second, we construct the pixel size control map using a convolution kernel method. Third, we utilize the pixel size control map to guide the foveated rendering. At last, a temporal coherent refinement strategy is used to maintain the smooth foveated rendering for the adjacent frames. Compared to the state-of-the-art mapping-based foveated rendering methods using the same compression ratio, our method achieves smaller MSE, higher PSNR, and SSIM in the fovea, periphery, salient regions, and the whole image. We also conducted user studies, and the results proved that the perceptual quality of our method has a high visual similarity with the around truth rendered with the full resolution.
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
场景感知凹凸渲染
我们提出了一种新的场景感知的有视点渲染方法,它将场景感知和人类视觉系统的特征融入到基于映射的有视点渲染框架中。首先,我们生成保守视觉重要性映射,该映射对场景的视觉特征、视觉敏锐度和注视运动进行编码。其次,我们使用卷积核方法构建像素尺寸控制图。第三,我们利用像素尺寸控制图来指导有焦点的渲染。最后,我们使用时间连贯细化策略来保持相邻帧的平滑凹陷渲染。在相同压缩比的情况下,与基于映射的最先进的有眼渲染方法相比,我们的方法在眼窝、外围、突出区域和整个图像中实现了更小的 MSE、更高的 PSNR 和 SSIM。我们还进行了用户研究,结果证明,我们的方法的感知质量与以全分辨率渲染的周围真相具有很高的视觉相似性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
DynAvatar: Dynamic 3D Head Avatar Deformation With Expression Guided Gaussian Splatting. Understanding the Research-Practice Gap in Visualization Design Guidelines. QuRAFT: Enhancing Quantum Algorithm Design by Visual Linking Between Mathematical Concepts and Quantum Circuits. DanceAgent: Dance Movement Refinement With LLM Agent. Do You "Trust" This Visualization? An Inventory to Measure Trust in Visualizations.
×
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:604180095
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