Smoothing Wavelet Reconstruction
| dc.contributor | Schaefer, Scott | |
| dc.creator | Garg, Deepak | |
| dc.date.accessioned | 2015-05-01T05:57:09Z | |
| dc.date.accessioned | 2017-04-07T20:04:40Z | |
| dc.date.available | 2015-05-01T05:57:09Z | |
| dc.date.available | 2017-04-07T20:04:40Z | |
| dc.date.created | 2013-05 | |
| dc.date.issued | 2013-04-23 | |
| 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. | |
| dc.identifier.uri | http://hdl.handle.net/1969.1/149509 | |
| dc.language.iso | en | |
| dc.subject | Surface reconstruction | |
| dc.subject | Graphics | |
| dc.subject | Wavelets | |
| dc.subject | Laplacian | |
| dc.title | Smoothing Wavelet Reconstruction | |
| dc.type | Thesis |