Spectral Analysis Driven Sparse Matching of 3D Shapes
| dc.contributor.author | Darom, Tal | en_US |
| dc.contributor.author | Keller, Yosi | en_US |
| dc.contributor.editor | M. Spagnuolo and M. Bronstein and A. Bronstein and A. Ferreira | en_US |
| dc.date.accessioned | 2013-09-24T10:53:07Z | |
| dc.date.available | 2013-09-24T10:53:07Z | |
| dc.date.issued | 2012 | en_US |
| dc.description.abstract | In this work we present an approach for matching three-dimensional mesh objects related by isometric transfor- mations and scaling. We propose to utilize the Scale invariant Scale-DoG detector and Local Depth SIFT mesh descriptor, to derive a statistical voting-based scheme to robustly estimate the scale ratio between the registered meshes. This paves the way to formulating a novel non-rigid mesh registration scheme, by matching sets of sparse salient feature points using spectral graph matching. The resulting approach is shown to compare favorably with previous state-of-the-art approaches in registering meshes related by partial alignment, while being a few orders of magnitude faster. | en_US |
| dc.description.sectionheaders | Posters | en_US |
| dc.description.seriesinformation | Eurographics Workshop on 3D Object Retrieval | en_US |
| dc.identifier.isbn | 978-3-905674-36-1 | en_US |
| dc.identifier.issn | 1997-0463 | en_US |
| dc.identifier.uri | https://doi.org/10.2312/3DOR/3DOR12/059-062 | en_US |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Spectral Analysis Driven Sparse Matching of 3D Shapes | en_US |
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