3D point of interest detection via spectral irregularity diffusion

Song, Ran, Liu, Yonghuai, Martin, Ralph and Rosin, Paul (2013) 3D point of interest detection via spectral irregularity diffusion. The Visual Computer, 29 (6-8). pp. 595-705. ISSN 0178-2789

Full content URL: http://dx.doi.org/10.1007/s00371-013-0806-4

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Item Type:Article
Item Status:Live Archive


This paper presents a method for detecting points of interest on 3D meshes. It comprises two major stages. In the first, we capture saliency in the spectral domain by detecting spectral irregularities of a mesh. Such saliency corresponds to the interesting portions of surface in the spatial domain. In the second stage, to transfer saliency information from the spectral domain to the spatial domain, we rely on spectral irregularity diffusion (SID) based on heat diffusion. SID captures not only the information about neighbourhoods of a given point in a multiscale manner, but also cues related to the global structure of a shape. It thus preserves information about both local and global saliency. We finally extract points of interest by looking for global and local maxima of the saliency map. We demonstrate the advantages of our proposed method using both visual and quantitative comparisons based on a publicly available benchmark.

Keywords:interest point, Mesh saliency, Points of interest, Laplacian, Eigendecomposition
Subjects:G Mathematical and Computer Sciences > G920 Others in Computing Sciences
Divisions:College of Science > School of Computer Science
ID Code:12530
Deposited On:11 Nov 2013 17:00

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