Heat Diffusion Approach for Feature-based Body Scans Analysis

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dc.contributor.authorLovato, Christianen_US
dc.contributor.authorZancanaro, C.en_US
dc.contributor.authorCastellani, Umbertoen_US
dc.contributor.authorGiachetti, Andreaen_US
dc.contributor.editorH. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkampen_US
dc.date.accessioned2013-04-25T14:10:26Z
dc.date.available2013-04-25T14:10:26Z
dc.date.issued2011en_US
dc.description.abstractIn this paper we propose the use of spectral shape analysis techniques for selection and classification of anthro- pometric points extracted from human-body scans. Few feature points are detected by exploiting the capability of heat diffusion process in capturing the extremities of surface protrusions which are often related to anthropometric landmarks. Then, a heat kernel signature is computed for each feature point which are associated to its seman- tic group by employing a learning-by-example procedure exploiting manual point labeling provided by an expert anthropometrist. Detected points are not clearly the same precise anatomical locations used in standard anthro- pometric procedures, but their matching can be useful for different applications like automatic model registration or simple body type evaluation. Experimental tests carried out on several subjects with different anthropometric characteristics show encouraging results demonstrating the potential usefulness of the approach as well as the necessity of further investigation on point description and matching.en_US
dc.description.sectionheadersNon-rigid Shape Matching and Retrievalen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-31-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR11/033-040en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modelingen_US
dc.titleHeat Diffusion Approach for Feature-based Body Scans Analysisen_US
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