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Mesh Saliency via Spectral Processing R. Song, Y.-H. Liu, R. R. Martin, P. L. Rosin ACM Transactions on Graphics 33 (1), Article 6, 2014.

Mesh Saliency via Spectral Processing
R. Song, Y.-H. Liu, R. R. Martin, P. L. Rosin
ACM Transactions on Graphics 33 (1), Article 6, 2014.

We propose a novel method for detecting mesh saliency, a perceptuallybased measure of the importance of a local region on a 3D surface mesh.

Our method incorporates global considerations by making use of spectral attributes of the mesh, unlike most existing methods which are typically based on local geometric cues. We first consider the properties of the log-Laplacian spectrum of the mesh. Those frequencies which show differences from expected behaviour capture saliency in the frequency domain. Information
about these frequencies is considered in the spatial domain at multiple spatial scales to localise the salient features and give the final salient areas. The effectiveness and robustness of our approach are demonstrated by comparisons to previous approaches on a range of test models. The benefits of the proposed method are further evaluated in applications such as mesh simplification, mesh segmentation and scan integration, where we show how incorporating mesh saliency can provide improved results.

Link to Paper

Authors

Dr Yonghuai Liu

Dr Yonghuai Liu

3D imaging, analysis and applications

Prof. Ralph Martin

Prof. Ralph Martin

Polygon mesh processing including registration, noise removal, segmentation and surface fitting.

Prof. Paul Rosin

Prof. Paul Rosin

Various aspects of computer vision, including 2D and 3D facial analysis and synthesis.