Keywords
View Synthesis, View Morphing, ATR, EOIR
Abstract
View Synthesis is the challenging problem of predicting a new view or pose of an object given an exemplar view or set of views. This thesis presents a novel approach for the problem of view synthesis. The proposed method uses global features rather than local geometry to achieve an effect similar to that of the well known view morphing method . While previous approaches to the view synthesis problem have shown impressive results, they are highly dependent on being able to solve for epipolar geometry and therefore have a very precise correspondence between reference images. In cases where this is not possible such as noisy data, low contrast data, or long wave infrared data an alternative approach is desirable. Here two problems will be considered. The proposed view synthesis method will be used to synthesis new views given a set of reference views. Additionally the algorithm will be extended to synthesis new lighting conditions and thermal signatures. Finally the algorithm will be applied toward enhancing the ATR problem by creating additional training data to increase the likelihood of detection and classification.
Notes
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
Graduation Date
2009
Advisor
Shah, Mubarak
Degree
Master of Science in Electrical Engineering (M.S.E.E.)
College
College of Engineering and Computer Science
Department
Electrical Engineering and Computer Science
Degree Program
Electrical Engineering
Format
application/pdf
Identifier
CFE0002684
URL
http://purl.fcla.edu/fcla/etd/CFE0002684
Language
English
Release Date
September 2009
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
STARS Citation
Berkowitz, Phillip, "A Statistical Approach To View Synthesis" (2009). Electronic Theses and Dissertations. 4173.
https://stars.library.ucf.edu/etd/4173