JOURNAL ARTICLE

Scene-aware Foveated Rendering

Runze FanXuehuai ShiKangyu WangQixiang MaLili Wang

Year: 2024 Journal:   IEEE Transactions on Visualization and Computer Graphics Vol: 30 (11)Pages: 7097-7106   Publisher: Institute of Electrical and Electronics Engineers

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.

Keywords:
Computer science Computer graphics (images) Rendering (computer graphics) Computer vision Artificial intelligence Image-based modeling and rendering Visualization Real-time rendering Tiled rendering Alternate frame rendering Software rendering Computer graphics 3D computer graphics

Metrics

10
Cited By
12.76
FWCI (Field Weighted Citation Impact)
38
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Computer Graphics and Visualization Techniques
Physical Sciences →  Computer Science →  Computer Graphics and Computer-Aided Design
3D Shape Modeling and Analysis
Physical Sciences →  Engineering →  Computational Mechanics
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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