Smooth Reverse Subdivision

atmire.migration.oldid965
dc.contributor.advisorSamavati, Faramarz
dc.contributor.authorSadeghi, Javad
dc.date.accessioned2013-05-06T15:43:13Z
dc.date.available2013-06-10T07:00:47Z
dc.date.issued2013-05-06
dc.date.submitted2013en
dc.description.abstractMultiresolution (MR) provides a useful framework for hierarchical representation and manipulation of geometric objects. It consists of two main operations: decomposition (finding coarse points and details) and reconstruction (subdivision plus error correction). One way to construct MR is to use a reverse subdivision (RS) approach by minimizing the error between fine points and subdivided coarse points. However, after a few levels of decomposition using current RS techniques, the coarse points are usually high energy and do not preserve the overall structure of the fine points. This limits the reverse subdivision-based editing and synthesis applications to produce accurate results. This thesis introduces a new reverse subdivision framework, entitled "Smooth Reverse Subdivision", that considers the smoothness of the coarse points as a factor in the decomposition. Using a weighted least-squares approach, a trial set of reverse subdivision operations are optimized globally to have a balance between providing a good approximation of the fine points and reducing the energy of the coarse points. Then, by finding a local representation for the resulting operations, the work is extended to subdivision schemes for general topology surfaces. The resulting decomposition and reconstruction operations feature linear processing time. To achieve a compact representation for these operations, a novel fairing operation with local inverse is presented. The new decomposition operations resulting from this new fairing technique can be reversed locally without over-representation. In addition, the new fairing operation provides a well-defined structure for constructing new subdivision and reverse subdivision schemes. Finally, smooth reverse subdivision is used in example MR editing and synthesis applications as well as image compression. Smooth coarse models resulting from this work, preserve the overall structure of the fine models. This improves the results of current MR editing and synthesis applications.en_US
dc.identifier.citationSadeghi, J. (2013). Smooth Reverse Subdivision (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27806en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/27806
dc.identifier.urihttp://hdl.handle.net/11023/701
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.facultyScience
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectComputer Science
dc.subject.classificationMultiresolutionen_US
dc.subject.classificationReverse subdivisionen_US
dc.subject.classificationEnergy minimizationen_US
dc.titleSmooth Reverse Subdivision
dc.typedoctoral thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
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