Variational image processing algorithms for the stereoscopic space-time reconstruction of water waves

Gallego Bonet, Guillermo

Title:

Variational image processing algorithms for the stereoscopic space-time reconstruction of water waves

dc.contributor.advisor	Yezzi, Anthony
dc.contributor.advisor	Fedele, Francesco
dc.contributor.author	Gallego Bonet, Guillermo	en_US
dc.contributor.committeeMember	Dellaert, Frank
dc.contributor.committeeMember	Egerstedt, Magnus
dc.contributor.committeeMember	Tannenbaum, Allen
dc.contributor.committeeMember	Vela, Patricio
dc.contributor.department	Electrical and Computer Engineering	en_US
dc.date.accessioned	2011-07-06T16:25:02Z
dc.date.available	2011-07-06T16:25:02Z
dc.date.issued	2011-01-19	en_US
dc.description.abstract	A novel video observational method for the space-time stereoscopic reconstruction of dynamic surfaces representable as graphs, such as ocean waves, is developed. Variational optimization algorithms combining image processing, computer vision and partial differential equations are designed to address the problem of the recovery of the shape of an object's surface from sequences of synchronized multi-view images. Several theoretical and numerical paths are discussed to solve the problem. The variational stereo method developed in this thesis has several advantages over existing 3-D reconstruction algorithms. Our method follows a top-down approach or object-centered philosophy in which an explicit model of the target object in the scene is devised and then related to image measurements. The key advantages of our method are the coherence (smoothness) of the reconstructed surface caused by a coherent object-centered design, the robustness to noise due to a generative model of the observed images, the ability to handle surfaces with smooth textures where other methods typically fail to provide a solution, and the higher resolution achieved due to a suitable graph representation of the object's surface. The method provides competitive results with respect to existing variational reconstruction algorithms. However, our method is based upon a simplified but complete physical model of the scene that allows the reconstruction process to include physical properties of the object's surface that are otherwise difficult to take into account with existing reconstruction algorithms. Some initial steps are taken toward incorporating the physics of ocean waves in the stereo reconstruction process. The developed method is applied to empirical data of ocean waves collected at an off-shore oceanographic platform located off the coast of Crimea, Ukraine. An empirically-based physical model founded upon current ocean engineering standards is used to validate the results. Our findings suggest that this remote sensing observational method has a broad impact on off-shore engineering to enrich the understanding of sea states, enabling improved design of off-shore structures. The exploration of ways to incorporate dynamical properties, such as the wave equation, in the reconstruction process is discussed for future research.	en_US
dc.description.degree	Ph.D.	en_US
dc.identifier.uri	http://hdl.handle.net/1853/39480
dc.publisher	Georgia Institute of Technology	en_US
dc.subject	Multigrid methods	en_US
dc.subject	Marine technology	en_US
dc.subject	Remote sensing	en_US
dc.subject	Image processing	en_US
dc.subject	Stereo vision	en_US
dc.subject	Ocean waves	en_US
dc.subject	Variational methods	en_US
dc.subject.lcsh	Imaging systems
dc.subject.lcsh	Water waves
dc.title	Variational image processing algorithms for the stereoscopic space-time reconstruction of water waves	en_US
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Yezzi, Anthony
local.contributor.corporatename	School of Electrical and Computer Engineering
local.contributor.corporatename	College of Engineering
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