Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics
This work addresses the need for better human perception modeling in 3D graphics, particularly for textured meshes, though it is incremental by building on existing mesh saliency studies.
The paper tackles the problem of predicting saliency on textured 3D meshes by introducing a new dataset from eye-tracking in VR and a model that integrates texture and geometry, achieving improved accuracy in saliency prediction for applications like VR and gaming.
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.