Given the complexity of the complete process, difficulties arise mainly in three stages: the decomposition of the image based reconstruction process, the accurate estimation of the camera positions and the semantic interpretation of the resulting model.
This thesis deals with the problem of large scale city-size reconstruction and modeling using a monocular camera. The goal of the research was twofold. Firstly, to obtain an accurate, fast and inexpensive method to perform 3D reconstruction. Secondly, to obtain a semantic model of the reconstructed environment.
We decompose the reconstruction procedure and design a processing pipeline for 3D reconstruction of urban areas by exploring the range of algorithms and methodology choices. By careful reasoning and comparison of state-of- the-art methods we are able to optimize the results of the algorithms involved. We propose an algorithm for estimating optimally, and in closed form, the scaled translation of a camera with as little as one correspondence between the 3D space and the 2D image space. Finally, we approach the problem of semantic modeling of large urban areas by merging information from different sources to reach a detailed building level description.
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library, or send a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.