Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics

Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment, education, and industry. While traditional mesh saliency studies focus on non-textured meshes, our work explores the complexities introduced by detailed texture patterns. We present a new dataset for textured mesh saliency, created through an innovative eye-tracking experiment in a six degrees of freedom (6-DOF) VR environment. This dataset addresses the limitations of previous studies by providing comprehensive eye-tracking data from multiple viewpoints, thereby advancing our understanding of human visual behavior and supporting more accurate and effective 3D content creation. Our proposed model predicts saliency maps for textured mesh surfaces by treating each triangular face as an individual unit and assigning a saliency density value to reflect the importance of each local surface region. The model incorporates a texture alignment module and a geometric extraction module, combined with an aggregation module to integrate texture and geometry for precise saliency prediction. We believe this approach will enhance the visual fidelity of geometric processing while ensuring computational efficiency, essential for real-time rendering and high-detail applications such as VR and gaming.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i9.33082
Citations
2
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
3.12
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article

Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics

Dandan Zhu, Kaiwei Zhang, Xiongkuo Min, Guangtao Zhai
2 citations
Proceedings of the AAAI Conference on Artificial Intelligence
3D Shape Modeling and Analysis
3.12
article

Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics

Dandan Zhu, Kaiwei Zhang, Xiongkuo Min, Guangtao Zhai
article en
2 citations

Abstract

Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment, education, and industry. While traditional mesh saliency studies focus on non-textured meshes, our work explores the complexities introduced by detailed texture patterns. We present a new dataset for textured mesh saliency, created through an innovative eye-tracking experiment in a six degrees of freedom (6-DOF) VR environment. This dataset addresses the limitations of previous studies by providing comprehensive eye-tracking data from multiple viewpoints, thereby advancing our understanding of human visual behavior and supporting more accurate and effective 3D content creation. Our proposed model predicts saliency maps for textured mesh surfaces by treating each triangular face as an individual unit and assigning a saliency density value to reflect the importance of each local surface region. The model incorporates a texture alignment module and a geometric extraction module, combined with an aggregation module to integrate texture and geometry for precise saliency prediction. We believe this approach will enhance the visual fidelity of geometric processing while ensuring computational efficiency, essential for real-time rendering and high-detail applications such as VR and gaming.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(9)
Shanghai Jiao Tong University (CN), East China Normal University (CN)
Openalex Percentile: Top 7%
3D Shape Modeling and Analysis
3.12
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