Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/24788
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dc.coverage.spatialInformation and Communication Engineeringen_US
dc.date.accessioned2014-09-09T06:18:58Z-
dc.date.available2014-09-09T06:18:58Z-
dc.date.issued2014-09-09-
dc.identifier.urihttp://hdl.handle.net/10603/24788-
dc.description.abstractThe Interactive 3D Computer Graphics has gained attention over the network in recent times through various 3D Networked Virtual Environments such as Massively Multi user Online Games Virtual Universities Virtual Museums and 3D Art Galleries These 3D networked virtual environments comprise of a set of 3D objects characterized by high resolution meshes On demand the client has to wait longer until these high resolution meshes are completely downloaded for every request In order to reduce this waiting time client server frameworks have been defined to progressively stream visible portion of the 3D content based on user interaction pattern predictions The streamed 3D content is newlinerendered on to a client machine Thus in addition to the idea of progressive streaming and rendering of visible meshes the anticipatory streaming of additional meshes in advance based on the user interaction pattern is proposed In this work anticipatory streaming model is referred as Predictive Streaming Predictive Streaming would thus help in effective utilization of the network bandwidth client memory and reduce rendering latency In this thesis the mesh attributes of 3D models which carry the dominant features for 3D reconstruction are considered for implementation and analysis of streaming and rendering The meshes which are triangular geometry shapes of newlinethe 3D objects comprise of vertices and its connectivity newline newlineen_US
dc.format.extentxxii, 235p.en_US
dc.languageEnglishen_US
dc.relation-en_US
dc.rightsuniversityen_US
dc.titleNew approaches for 3D streaming and rendering based on predictive modelingen_US
dc.title.alternative-en_US
dc.creator.researcherVani, Ven_US
dc.subject.keyword3D streamingen_US
dc.subject.keywordBayes Probabilistic Modelen_US
dc.subject.keywordComputer Graphicsen_US
dc.subject.keywordInformation and communication engineeringen_US
dc.subject.keywordMarkov Chain Modelen_US
dc.description.noteAppendix p.187-215, References p.216-232en_US
dc.contributor.guidePradeep Kumar, Ren_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d.en_US
dc.date.completed01/09/2013en_US
dc.date.awarded30/09/2013en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File25.17 kBAdobe PDFView/Open
02_certificate.pdf399.93 kBAdobe PDFView/Open
03_abstract.pdf8.11 kBAdobe PDFView/Open
04_acknowledgement.pdf5.96 kBAdobe PDFView/Open
05_contents.pdf70.4 kBAdobe PDFView/Open
06_chapter1.pdf1.01 MBAdobe PDFView/Open
07_chapter2.pdf1.48 MBAdobe PDFView/Open
08_chapter3.pdf388.44 kBAdobe PDFView/Open
09_chapter4.pdf1.08 MBAdobe PDFView/Open
11_chapter6.pdf2.39 MBAdobe PDFView/Open
12_chapter7.pdf20.09 kBAdobe PDFView/Open
13_appendix.pdf1.08 MBAdobe PDFView/Open
14_references.pdf62.94 kBAdobe PDFView/Open
15_publications.pdf9.6 kBAdobe PDFView/Open
16_vitae.pdf6.64 kBAdobe PDFView/Open


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