3D Object Retrieval using an Efficient and Compact Hybrid Shape Descriptor

dc.contributor.authorPapadakis, Panagiotisen_US
dc.contributor.authorPratikakis, Ioannisen_US
dc.contributor.authorTheoharis, Theoharisen_US
dc.contributor.authorPassalis, Georgiosen_US
dc.contributor.authorPerantonis, Stavrosen_US
dc.contributor.editorStavros Perantonis and Nikolaos Sapidis and Michela Spagnuolo and Daniel Thalmannen_US
dc.date.accessioned2013-10-21T18:15:17Z
dc.date.available2013-10-21T18:15:17Z
dc.date.issued2008en_US
dc.description.abstractAbstract We present a novel 3D object retrieval method that relies upon a hybrid descriptor which is composed of 2D features based on depth buffers and 3D features based on spherical harmonics. To compensate for rotation, two alignment methods, namely CPCA and NPCA, are used while compactness is supported via scalar feature quantization to a set of values that is further compressed using Huffman coding. The superior performance of the proposed retrieval methodology is demonstrated through an extensive comparison against state-of-the-art methods on standard datasets.en_US
dc.description.seriesinformationEurographics 2008 Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-05-7en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR08/009-016en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.5.4 [Pattern Recognition]: Computer Vision, H.3.3 [Information Storage and Retrieval]: Information Search and Retrievalen_US
dc.title3D Object Retrieval using an Efficient and Compact Hybrid Shape Descriptoren_US
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