3D Geometry Coding using Mixture Models and the Estimation Quantization Algorithm

dc.citation.bibtexNamemastersthesisen_US
dc.citation.journalTitleMasters Thesisen_US
dc.contributor.authorLavu, Sridharen_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.creatorLavu, Sridharen_US
dc.date.accessioned2007-10-31T00:51:11Zen_US
dc.date.available2007-10-31T00:51:11Zen_US
dc.date.issued2002-09-01en_US
dc.date.modified2004-04-08en_US
dc.date.submitted2002-10-21en_US
dc.descriptionMasters Thesisen_US
dc.description.abstract3D surfaces are used in applications such as animations, 3D object modeling and visualization. The geometries of such surfaces are often approximated using polygonal meshes. This thesis aims to compress 3D geometry meshes by using an algorithm based on normal meshes and the Estimation-Quantization (EQ) algorithm. Normal meshes are multilevel representations where finer level vertices lie in a direction normal to the local surface and therefore compress the vertex data to one scalar value per vertex. A mixture distribution model is used for the wavelet coefficients. The EQ algorithm uses the local neighborhood information and Rate-Distortion optimization to encode the wavelet coefficients. We achieve performance gains of 0.5-1dB compared to the zerotree coder for normal meshes.en_US
dc.identifier.citationS. Lavu, "3D Geometry Coding using Mixture Models and the Estimation Quantization Algorithm," Masters Thesis, 2002.en_US
dc.identifier.urihttps://hdl.handle.net/1911/20050en_US
dc.language.isoengen_US
dc.subject3D geometryen_US
dc.subjectnormal meshesen_US
dc.subjectEQ coderen_US
dc.subjectgeometry processingen_US
dc.subject.keyword3D geometryen_US
dc.subject.keywordnormal meshesen_US
dc.subject.keywordEQ coderen_US
dc.subject.keywordgeometry processingen_US
dc.subject.otherWavelet based Signal/Image Processingen_US
dc.subject.otherMultiscale Methodsen_US
dc.subject.otherMultiscale geometry processingen_US
dc.title3D Geometry Coding using Mixture Models and the Estimation Quantization Algorithmen_US
dc.typeThesisen_US
dc.type.dcmiTexten_US
dc.type.dcmiTexten_US
thesis.degree.levelMastersen_US
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