Visual saliency guided textured model simplification

Abstract

The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract Mesh geometry can be used to model both object shape and details. If texture maps are involved, it is common to let mesh geometry mainly model object shapes and use texture maps modelling most object details, optimising data size and complexity of an object. To support efficient object rendering and transmission, model simplification can be applied to reduce the modelling data. However, existing methods do not well consider how object features are jointly represented by mesh geometry and texture maps, having problems in identifying and preserving important features for simplified objects. To address this, we propose a visual saliency detection method for simplifying textured 3D models. We produce good simplification results by jointly processing mesh geometry and texture map to generate a unified saliency map for identifying visually important object features. Results show our method offers a better object rendering quality than existing methods.

Compressed dynamic mesh sequence for progressive streaming

“…For future work, we plan to use the Spatio‐temporal Edge Difference (STED) metric to measure our results. Also, we would like to consider using deep learning methods to detect saliency of a DMS, formulating a method to improve DMS compression rate.…”

Saliency guided adaptive image abstraction

“…Yang et al proposed that saliency can also be used for simplification of 3D textured models [13]. Non-linear filters such as bilateral filter, difference of Gaussian filter, Kuwahara filter and morphological filters, and partial differential equation based methods such as anisotropic diffusion ( [14], [15]), and mean curvature flow have also actively been used recently for image abstraction [16].…”

Perception-driven Accelerated Rendering

“…The authors introduce a multi‐scale shape descriptor to estimate saliency locally, and in a rotationally invariant way. Yang et al [YLW*16] combine mesh saliency with texture contrast resulting in saliency texture, which is used to simplify textured models (Fig. ).…”

“…Mesh saliency method by Yang et al [YLW*16]. The approach takes a textured mesh (a),(b) and measures local geometric entropy (c), color and intensity (d).…”