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Smoothing Wavelet Reconstruction
dc.contributor.advisor | Schaefer, Scott | |
dc.creator | Garg, Deepak | |
dc.date.accessioned | 2013-10-03T15:02:50Z | |
dc.date.available | 2015-05-01T05:57:09Z | |
dc.date.created | 2013-05 | |
dc.date.issued | 2013-04-23 | |
dc.date.submitted | May 2013 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/149509 | |
dc.description.abstract | This thesis present a new algorithm for creating high quality surfaces from large data sets of oriented points, sampled using a laser range scanner. This method works in two phases. In the first phase, using wavelet surface reconstruction method, we calculate a rough estimate of the surface in the form of Haar wavelet coefficients, stored in an Octree. In the second phase, we modify these coefficients to obtain a higher quality surface. We cast this method as a gradient minimization problem in the wavelet domain. We show that the solution to the gradient minimization problem, in the wavelet domain, is a sparse linear system with dimensionality roughly proportional to the surface of the model in question. We introduce a fast inplace method, which uses various properties of Haar wavelets, to solve the linear system and demonstrate the results of the algorithm. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.subject | Surface reconstruction | en |
dc.subject | Graphics | en |
dc.subject | Wavelets | en |
dc.subject | Laplacian | en |
dc.title | Smoothing Wavelet Reconstruction | en |
dc.type | Thesis | en |
thesis.degree.department | Computer Science and Engineering | en |
thesis.degree.discipline | Computer Science | en |
thesis.degree.grantor | Texas A&M University | en |
thesis.degree.name | Master of Science | en |
thesis.degree.level | Masters | en |
dc.contributor.committeeMember | Keyser, John | |
dc.contributor.committeeMember | Chai, Jinxiang | |
dc.contributor.committeeMember | Akleman, Ergun | |
dc.type.material | text | en |
dc.date.updated | 2013-10-03T15:02:50Z | |
local.embargo.terms | 2015-05-01 |
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