Saliency detection of textured 3D models based on multi-view information and texel descriptor.

ABSTRACT: Saliency-driven mesh simplification methods have shown promising results in maintaining visual detail, but effective simplification requires accurate 3D saliency maps. The conventional mesh saliency detection method may not capture salient regions in 3D models with texture. To address this issue, we propose a novel saliency detection method that fuses saliency maps from multi-view projections of textured models. Specifically, we introduce a texel descriptor that combines local convexity and chromatic aberration to capture texel saliency at multiple scales. Furthermore, we created a novel dataset that reflects human eye fixation patterns on textured models, which serves as an objective evaluation metric. Our experimental results demonstrate that our saliency-driven method outperforms existi

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC10703070 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature