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 algorithms while ensuring efficient use of computational resources, which is crucial for real-time rendering and high-detail applications such as VR and gaming.

翻译：纹理网格通过将精细的纹理细节映射到三维模型的几何结构上，显著提升了物体的真实感和细节表现。这一进展在娱乐、教育和工业等众多应用领域具有重要价值。传统网格显著性研究主要关注无纹理网格，而我们的工作则探讨了复杂纹理图案引入的新挑战。我们提出了一个新的纹理网格显著性数据集，该数据集通过一项创新的六自由度（6-DOF）虚拟现实环境眼动追踪实验创建。该数据集通过提供多视角的全面眼动追踪数据，弥补了先前研究的局限，从而深化了我们对人类视觉行为的理解，并支持更精准、高效的三维内容创作。我们提出的模型通过将每个三角面片视为独立单元，并为每个局部表面区域分配显著性密度值以反映其重要性，从而预测纹理网格表面的显著性图。该模型包含一个纹理对齐模块和一个几何特征提取模块，并结合一个聚合模块来整合纹理与几何信息，以实现精确的显著性预测。我们相信，这种方法将提升几何处理算法的视觉保真度，同时确保计算资源的高效利用，这对于虚拟现实和游戏等实时渲染与高细节应用至关重要。