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dc.contributor.authorDutagaci, Helinen_US
dc.contributor.authorCheung, Chun Panen_US
dc.contributor.authorGodil, Afzalen_US
dc.contributor.editorH. Laga and T. Schreck and A. Ferreira and A. Godil and I. Pratikakis and R. Veltkampen_US
dc.date.accessioned2013-04-25T14:10:27Z
dc.date.available2013-04-25T14:10:27Z
dc.date.issued2011en_US
dc.identifier.isbn978-3-905674-31-6en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttp://dx.doi.org/10.2312/3DOR/3DOR11/057-064en_US
dc.description.abstractIn this paper, we compare the results of five 3D interest point detection techniques to the interest points marked by human subjects. This comparison is used to quantitatively evaluate the interest point detection algorithms. We asked human subjects to look at a number of 3D models, and mark interest points on the models via a web-based interface. We propose a voting-based method to construct ground truth out of humans' selections of interest points. Evaluation measures, namely False Positive and False Negative Errors, are then defined based on the geodesic distance between the interest points detected by a particular algorithm and the human-generated ground truth.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation-Line and curve generationen_US
dc.titleEvaluation of 3D Interest Point Detection Techniquesen_US
dc.description.seriesinformationEurographics Workshop on 3D Object Retrievalen_US
dc.description.sectionheadersLocal Shape Descriptorsen_US


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