Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics
Kaiwei Zhang, Dandan Zhu, Xiongkuo Min, Guangtao Zhai

TL;DR
This paper introduces a new textured mesh saliency model that combines geometry and texture information, supported by a novel eye-tracking dataset in VR, to improve human perception modeling in 3D graphics.
Contribution
It presents a new dataset and a saliency prediction model that integrates texture and geometry for textured meshes, advancing understanding of visual attention in 3D environments.
Findings
The dataset captures comprehensive eye-tracking data in VR from multiple viewpoints.
The model effectively predicts saliency maps by combining texture and geometric features.
Enhanced accuracy in saliency prediction supports improved 3D content creation.
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…
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Taxonomy
Topics3D Shape Modeling and Analysis · 3D Surveying and Cultural Heritage
MethodsFocus
