SQ-Map: efficient layered collision detection and haptic rendering.
Identifieur interne : 001734 ( PubMed/Corpus ); précédent : 001733; suivant : 001735SQ-Map: efficient layered collision detection and haptic rendering.
Auteurs : Konstantinos Moustakas ; Dimitrios Tzovaras ; Michael Gerassimos StrintzisSource :
- IEEE transactions on visualization and computer graphics [ 1077-2626 ]
English descriptors
- KwdEn :
- Algorithms, Computer Graphics, Computer Simulation, Feedback (physiology), Hand (anatomy & histology), Hand (physiology), Humans, Image Enhancement (methods), Image Interpretation, Computer-Assisted (methods), Imaging, Three-Dimensional (methods), Information Storage and Retrieval (methods), Models, Biological, Software, Stress, Mechanical, Touch (physiology), User-Computer Interface.
- MESH :
- anatomy & histology : Hand.
- methods : Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Information Storage and Retrieval.
- physiology : Feedback, Hand, Touch.
- Algorithms, Computer Graphics, Computer Simulation, Humans, Models, Biological, Software, Stress, Mechanical, User-Computer Interface.
Abstract
This paper presents a novel layered and fast framework for real-time collision detection and haptic interaction in virtual environments based on superquadric virtual object modeling. An efficient algorithm is initially proposed for decomposing the complex objects into subobjects suitable for superquadric modeling, based on visual salience and curvature constraints. The distance between the superquadrics and the mesh is then projected onto the superquadric surface, thus generating a distance map (SQ-Map). Approximate collision detection is then performed by computing the analytical equations and distance maps instead of triangle per triangle intersection tests. Collision response is then calculated directly from the superquadric models and realistic smooth force feedback is obtained using analytical formulae and local smoothing on the distance map. Experimental evaluation demonstrates that SQ-Map reduces significantly the computational cost when compared to accurate collision detection methods and does not require the huge amounts of memory demanded by distance field-based methods. Finally, force feedback is calculated directly from the distance map and the superquadric formulae.
DOI: 10.1109/TVCG.2007.20
PubMed: 17093338
Links to Exploration step
pubmed:17093338Le document en format XML
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An efficient algorithm is initially proposed for decomposing the complex objects into subobjects suitable for superquadric modeling, based on visual salience and curvature constraints. The distance between the superquadrics and the mesh is then projected onto the superquadric surface, thus generating a distance map (SQ-Map). Approximate collision detection is then performed by computing the analytical equations and distance maps instead of triangle per triangle intersection tests. Collision response is then calculated directly from the superquadric models and realistic smooth force feedback is obtained using analytical formulae and local smoothing on the distance map. Experimental evaluation demonstrates that SQ-Map reduces significantly the computational cost when compared to accurate collision detection methods and does not require the huge amounts of memory demanded by distance field-based methods. Finally, force feedback is calculated directly from the distance map and the superquadric formulae.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">17093338</PMID><DateCreated><Year>2006</Year><Month>11</Month><Day>09</Day></DateCreated><DateCompleted><Year>2007</Year><Month>02</Month><Day>07</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Print">1077-2626</ISSN><JournalIssue CitedMedium="Print"><Volume>13</Volume><Issue>1</Issue><PubDate><MedlineDate>2007 Jan-Feb</MedlineDate></PubDate></JournalIssue><Title>IEEE transactions on visualization and computer graphics</Title><ISOAbbreviation>IEEE Trans Vis Comput Graph</ISOAbbreviation></Journal><ArticleTitle>SQ-Map: efficient layered collision detection and haptic rendering.</ArticleTitle><Pagination><MedlinePgn>80-93</MedlinePgn></Pagination><Abstract><AbstractText>This paper presents a novel layered and fast framework for real-time collision detection and haptic interaction in virtual environments based on superquadric virtual object modeling. An efficient algorithm is initially proposed for decomposing the complex objects into subobjects suitable for superquadric modeling, based on visual salience and curvature constraints. The distance between the superquadrics and the mesh is then projected onto the superquadric surface, thus generating a distance map (SQ-Map). Approximate collision detection is then performed by computing the analytical equations and distance maps instead of triangle per triangle intersection tests. Collision response is then calculated directly from the superquadric models and realistic smooth force feedback is obtained using analytical formulae and local smoothing on the distance map. Experimental evaluation demonstrates that SQ-Map reduces significantly the computational cost when compared to accurate collision detection methods and does not require the huge amounts of memory demanded by distance field-based methods. Finally, force feedback is calculated directly from the distance map and the superquadric formulae.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Moustakas</LastName><ForeName>Konstantinos</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Electrical and Computer Engineering Department, Aristotle University of Thessaloniki, University Campus, Thessaloniki, Greece. moustak@olympus.ee.auth.gr</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tzovaras</LastName><ForeName>Dimitrios</ForeName><Initials>D</Initials></Author><Author ValidYN="Y"><LastName>Strintzis</LastName><ForeName>Michael Gerassimos</ForeName><Initials>MG</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>IEEE Trans Vis Comput Graph</MedlineTA><NlmUniqueID>9891704</NlmUniqueID><ISSNLinking>1077-2626</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D000465">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003196">Computer Graphics</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D003198">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005246">Feedback</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006225">Hand</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000033">anatomy & histology</QualifierName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D007089">Image Enhancement</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D007090">Image Interpretation, Computer-Assisted</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D021621">Imaging, Three-Dimensional</DescriptorName><QualifierName MajorTopicYN="N" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D016247">Information Storage and Retrieval</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000379">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D008954">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012984">Software</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D013314">Stress, Mechanical</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014110">Touch</DescriptorName><QualifierName MajorTopicYN="Y" UI="Q000502">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D014584">User-Computer Interface</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2006</Year><Month>11</Month><Day>10</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2007</Year><Month>2</Month><Day>8</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2006</Year><Month>11</Month><Day>10</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="doi">10.1109/TVCG.2007.20</ArticleId><ArticleId IdType="pubmed">17093338</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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