Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88038
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dc.contributor.authorChen, Shuangminen
dc.contributor.authorLiu, Taijunen
dc.contributor.authorShu, Zhenyuen
dc.contributor.authorXin, Shiqingen
dc.contributor.authorHe, Yingen
dc.contributor.authorTu, Changheen
dc.contributor.editorPiras, Paoloen
dc.date.accessioned2018-03-07T01:04:08Zen
dc.date.accessioned2019-12-06T16:54:40Z-
dc.date.available2018-03-07T01:04:08Zen
dc.date.available2019-12-06T16:54:40Z-
dc.date.issued2018en
dc.identifier.citationChen, S., Liu, T., Shu, Z., Xin, S., He, Y., & Tu, C. (2018). Fast and robust shape diameter function. PLOS ONE, 13(1), e0190666-.en
dc.identifier.urihttps://hdl.handle.net/10356/88038-
dc.description.abstractThe shape diameter function (SDF) is a scalar function defined on a closed manifold surface, measuring the neighborhood diameter of the object at each point. Due to its pose oblivious property, SDF is widely used in shape analysis, segmentation and retrieval. However, computing SDF is computationally expensive since one has to place an inverted cone at each point and then average the penetration distances for a number of rays inside the cone. Furthermore, the shape diameters are highly sensitive to local geometric features as well as the normal vectors, hence diminishing their applications to real-world meshes which often contain rich geometric details and/or various types of defects, such as noise and gaps. In order to increase the robustness of SDF and promote it to a wide range of 3D models, we define SDF by offsetting the input object a little bit. This seemingly minor change brings three significant benefits: First, it allows us to compute SDF in a robust manner since the offset surface is able to give reliable normal vectors. Second, it runs many times faster since at each point we only need to compute the penetration distance along a single direction, rather than tens of directions. Third, our method does not require watertight surfaces as the input—it supports both point clouds and meshes with noise and gaps. Extensive experimental results show that the offset-surface based SDF is robust to noise and insensitive to geometric details, and it also runs about 10 times faster than the existing method. We also exhibit its usefulness using two typical applications including shape retrieval and shape segmentation, and observe a significant improvement over the existing SDF.en
dc.format.extent18 p.en
dc.language.isoenen
dc.relation.ispartofseriesPLOS ONEen
dc.rights© 2018 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.subjectNoiseen
dc.subjectAlgorithmen
dc.titleFast and robust shape diameter functionen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen
dc.identifier.doi10.1371/journal.pone.0190666en
dc.description.versionPublished versionen
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item.grantfulltextopen-
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