Keywords
imagery, 3D model, high-resolution, mapping, texture, feature
Abstract
Three-dimensional computer models, especially geospatial architectural data sets, can be visualized in the same way humans experience the world, providing a realistic, interactive experience. Scene familiarization, architectural analysis, scientific visualization, and many other applications would benefit from finely detailed, high resolution, 3D models. Automated methods to construct these 3D models traditionally has produced data sets that are often low fidelity or inaccurate; otherwise, they are initially highly detailed, but are very labor and time intensive to construct. Such data sets are often not practical for common real-time usage and are not easily updated. This thesis proposes Variable Resolution & Dimensional Mapping (VRDM), a methodology that has been developed to address some of the limitations of existing approaches to model construction from images. Key components of VRDM are texture palettes, which enable variable and ultra-high resolution images to be easily composited; texture features, which allow image features to integrated as image or geometry, and have the ability to modify the geometric model structure to add detail. These components support a primary VRDM objective of facilitating model refinement with additional data. This can be done until the desired fidelity is achieved as practical limits of infinite detail are approached. Texture Levels, the third component, enable real-time interaction with a very detailed model, along with the flexibility of having alternate pixel data for a given area of the model and this is achieved through extra dimensions. Together these techniques have been used to construct models that can contain GBs of imagery data.
Notes
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Graduation Date
2009
Advisor
Kasparis, Takis
Degree
Master of Science in Computer Engineering (M.S.Cp.E.)
College
College of Engineering and Computer Science
Department
Electrical Engineering and Computer Science
Degree Program
Computer Engineering
Format
application/pdf
Identifier
CFE0002837
URL
http://purl.fcla.edu/fcla/etd/CFE0002837
Language
English
Release Date
July 2014
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
STARS Citation
Venezia, Joseph, "Variable Resolution & Dimensional Mapping For 3d Model Optimization" (2009). Electronic Theses and Dissertations. 4167.
https://stars.library.ucf.edu/etd/4167