Abstract
Current state of the art suggests the use of variational formulations for solving a variety of computer vision problems. This thesis deals with such variational problems which often include the optimization of curves and surfaces. The level set method is used throughout the work, both as a tool in the theoretical analysis and for constructing practical algorithms. One frequently occurring example is the problem of recovering threedimensional (3D) models of a scene given only a sequence of images. Other applications such as segmentation are also considered.
The thesis consists of three parts. The first part contains a review of background material and the level set method. The second part contains a collection of theoretical contributions such as a gradient descent framework and an analysis of several variational curve and surface problems. The third part contains contributions for applications such as a framework for open surfaces and variational surface fitting to different types of data.
The thesis consists of three parts. The first part contains a review of background material and the level set method. The second part contains a collection of theoretical contributions such as a gradient descent framework and an analysis of several variational curve and surface problems. The third part contains contributions for applications such as a framework for open surfaces and variational surface fitting to different types of data.
Original language  English 

Qualification  Doctor 
Awarding Institution 

Supervisors/Advisors 

Award date  2006 Sept 29 
Publisher  
ISBN (Print)  9789162869267 
Publication status  Published  2006 
Bibliographical note
Defence detailsDate: 20060929
Time: 13:15
Place: Ubåtshallen, i sal U:301, Malmö Högskola
External reviewer(s)
Name: Paragios, Nikos
Title: Professor
Affiliation: Ecole Centrale de Paris, Frankrike

Subject classification (UKÄ)
 Mathematics
Free keywords
 Mathematics
 level set methods
 computer vision
 variational problems
 Matematik