We propose a new method for detecting mesh saliency, a reflection of perception-based regional importance for 3D meshes. The basic idea is to incorporate the Conditional Random Field (CRF) framework with a saliency detection process. We first produce a multi-scale representation for a mesh. Then, a CRF is designed to robustly detect salient regions utilising neighbourhood consistency. By inferring the CRF via belief propagation algorithm, we actually make use of the global statistic information in the saliency detection process. Experimental results demonstrate the robustness and the effectiveness of the proposed method. Index Terms — Saliency, CRF, Mesh Simplification 1
Narayan V, Tscherepanow M, Wrede B. A saliency map based on sampling an image into random rectangula...
International audienceMany computer graphics applications use visual saliency information to guide t...
International audienceMesh surface saliency detection is an important preprocessing step for many 3D...
We propose a new method for detecting mesh saliency, a reflection of perception-based regional impor...
We propose a novel multiscale saliency detection algorithm for 3D meshes based on random walk framew...
Salient object detection is aimed at detecting and segmenting objects that human eyes are most focus...
In this paper, a unified detection algorithm of viewindependent and view-dependent saliency for 3D m...
In this paper, we propose an accurate and robust approach to salient region detection for 3D polygon...
As a measure of regional importance in agreement with human perception of 3D shape, mesh saliency sh...
In this paper, we propose an accurate and robust approach to salient region detection for 3D polygon...
Mesh surface saliency detection is an important preprocessing step for many 3D applications. The sal...
The detection of salient regions is an important pre-processing step for many 3D shape analysis and ...
International audienceOur visual attention is attracted by specific areas into 3D objects (represent...
We present a novel approach for estimating mesh saliency. Our method is fast, flexible, and easy to ...
Visual Saliency Estimation is a computer vision problem that aims to find the regions of interest th...
Narayan V, Tscherepanow M, Wrede B. A saliency map based on sampling an image into random rectangula...
International audienceMany computer graphics applications use visual saliency information to guide t...
International audienceMesh surface saliency detection is an important preprocessing step for many 3D...
We propose a new method for detecting mesh saliency, a reflection of perception-based regional impor...
We propose a novel multiscale saliency detection algorithm for 3D meshes based on random walk framew...
Salient object detection is aimed at detecting and segmenting objects that human eyes are most focus...
In this paper, a unified detection algorithm of viewindependent and view-dependent saliency for 3D m...
In this paper, we propose an accurate and robust approach to salient region detection for 3D polygon...
As a measure of regional importance in agreement with human perception of 3D shape, mesh saliency sh...
In this paper, we propose an accurate and robust approach to salient region detection for 3D polygon...
Mesh surface saliency detection is an important preprocessing step for many 3D applications. The sal...
The detection of salient regions is an important pre-processing step for many 3D shape analysis and ...
International audienceOur visual attention is attracted by specific areas into 3D objects (represent...
We present a novel approach for estimating mesh saliency. Our method is fast, flexible, and easy to ...
Visual Saliency Estimation is a computer vision problem that aims to find the regions of interest th...
Narayan V, Tscherepanow M, Wrede B. A saliency map based on sampling an image into random rectangula...
International audienceMany computer graphics applications use visual saliency information to guide t...
International audienceMesh surface saliency detection is an important preprocessing step for many 3D...