3D point of interest detection via spectral irregularity diffusion

Song, Ran, Liu, Yonghuai, Martin, Ralph Robert and Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884 2013. 3D point of interest detection via spectral irregularity diffusion. The Visual Computer 29 (6-8) , pp. 695-705. 10.1007/s00371-013-0806-4

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Abstract

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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Uncontrolled Keywords:	Mesh saliency; Points of interest; Laplacian; Eigendecomposition
Additional Information:	Pdf uploaded in accordance with publisher's policy at http://www.sherpa.ac.uk/romeo/issn/0178-2789/ (accessed 23/10/14) The final publication is available at Springer via http://dx.doi.org/10.1007/s00371-013-0806-4
Publisher:	Springer
ISSN:	0178-2789
Date of First Compliant Deposit:	30 March 2016
Last Modified:	20 Nov 2024 03:45
URI:	https://orca.cardiff.ac.uk/id/eprint/50740

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