Efficient Optimization Techniques for Localization and Registration of Images

This thesis focuses on two problems in the field of computer vision and image analysis. The first part of the thesis deals with image localization. The goal is simply to answer the question: Where was this picture taken? To answer this two things are needed: A model of the world, or at least the relevant parts of the world, and a method for relating a new image to the model. The thesis presents new methods for both steps, based on modern optimization methods. By taking advantage of additional sensors, such as GPS or gravity sensors, higher precision and reliability is achieved compared to previous methods. The second part of the thesis is concerned with the problem of image registration, with focus on medical applications. The goal of image registration is to find the correct transformation between two images depicting the same, or similar, objects. The new methods presented in this thesis aim at increasing robustness in the sense of easy accommodation to new applications without manual adjustment. Several of the methods also aim to increase reliability, i.e. to be able to find good solutions, even if the data contains high levels of noise and outlier structures