Audio-Visual Aware Foveated Rendering

With the increasing complexity of geometry and rendering effects in virtual reality (VR) scenes, existing foveated rendering methods for VR head-mounted displays (HMDs) struggle to meet users' demands for VR scene rendering with high frame rates ($\geq 60fps$≥60fps for rendering binocular foveated images in VR scenes containing over 50 m triangles). Current research validates that auditory content affects the perception of the human visual system (HVS). However, existing foveated rendering methods primarily model the HVS's eccentricity-dependent visual perception ability on the visual content in VR while ignoring the impact of auditory content on the HVS's visual perception. In this article, we introduce an auditory-content-based perceived rendering quality analysis to quantify the impact of visual perception under different auditory conditions in foveated rendering. Based on the analysis results, we propose an audio-visual aware foveated rendering method (AvFR). AvFR first constructs an audio-visual feature-driven perception model that predicts the eccentricity-based visual perception in real time by combining the scene's audio-visual content, and then proposes a foveated rendering cost optimization algorithm to adaptively control the shading rate of different regions with the guidance of the perception model. In complex scenes with visual and auditory content containing over 1.17 m triangles, AvFR renders high-quality binocular foveated images at an average frame rate of 116$fps$fps. The results of the main user study and performance evaluation validate that AvFR achieves significant performance improvement (up to 1.4× speedup) without lowering the perceived visual quality compared with the state-of-the-art VR-HMD foveated rendering method.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-03-26
DOI
https://doi.org/10.1109/tvcg.2025.3554737
Primary Topic
Computer Graphics and Visualization Techniques
Type
article
Field-Weighted Citation Impact
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article

Audio-Visual Aware Foveated Rendering

Xuehuai Shi, Xiaobai Chen, Yucheng Li, Jieming Yin et al.
IEEE Transactions on Visualization and Computer Graphics
Computer Graphics and Visualization Techniques
article

Audio-Visual Aware Foveated Rendering

Xuehuai Shi, Xiaobai Chen, Yucheng Li, Jieming Yin, Lili Wang, Jiaheng Li, Jian Wu
article en

Abstract

With the increasing complexity of geometry and rendering effects in virtual reality (VR) scenes, existing foveated rendering methods for VR head-mounted displays (HMDs) struggle to meet users' demands for VR scene rendering with high frame rates ($\geq 60fps$≥60fps for rendering binocular foveated images in VR scenes containing over 50 m triangles). Current research validates that auditory content affects the perception of the human visual system (HVS). However, existing foveated rendering methods primarily model the HVS's eccentricity-dependent visual perception ability on the visual content in VR while ignoring the impact of auditory content on the HVS's visual perception. In this article, we introduce an auditory-content-based perceived rendering quality analysis to quantify the impact of visual perception under different auditory conditions in foveated rendering. Based on the analysis results, we propose an audio-visual aware foveated rendering method (AvFR). AvFR first constructs an audio-visual feature-driven perception model that predicts the eccentricity-based visual perception in real time by combining the scene's audio-visual content, and then proposes a foveated rendering cost optimization algorithm to adaptively control the shading rate of different regions with the guidance of the perception model. In complex scenes with visual and auditory content containing over 1.17 m triangles, AvFR renders high-quality binocular foveated images at an average frame rate of 116$fps$fps. The results of the main user study and performance evaluation validate that AvFR achieves significant performance improvement (up to 1.4× speedup) without lowering the perceived visual quality compared with the state-of-the-art VR-HMD foveated rendering method.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(10)
Nanjing University of Posts and Telecommunications (CN), Beihang University (CN)
Openalex Percentile: Top 90%
Computer Graphics and Visualization Techniques
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