Προγραμματισμός και αξιολόγηση φωτοτριγωνισμού με αυτοβαθμονόμηση σε εικόνες άγνωστης διάταξης - Κακογιάννου, Μαρία (Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Αγρονόμων και Τοπογράφων Μηχανικών. Τομέας Τοπογραφίας. Εργαστήριο Φωτογραμμετρίας, 2017)
Due to the groundbreaking research in the field of Computer Vision, in the field of Digital Photogrammetry there is an effort towards the full automation of photogrammetric processes. In this framework, main idea of this Diploma Thesis is the way to utilize the providing algorithms, computational techniques and concepts which make faster and easier implementations feasible. Main subject of this Thesis is the development and evaluation of fully automatic self-calibrating bundle adjustment in sets of unordered images. In more detail, based on sets of successive overlapping images, the implemented algorithm is capable of automatically estimating the orientation parameters of all images in some arbitrary system, the camera parameters (interior orientation) and the3D coordinates of reconstructed points in this system. In order, to achieve the main purpose of this Thesis, corresponding interest points are initially detected on every image pair with the SIFT point operator. The invalid correspondences are rejected by the LMS (Least Mean Squares) algorithm in combination with the Fundamental matrix, from which the camera focal length is linearly determined. As a result, the program proceeds to the calculation per image pair of approximate values, which are needed for the final multi-image bundle adjustment. This is achieved at first by using linear algorithms (decomposition of essential matrix) and subsequently by using the coplanarity condition. All points that are common to pairs are then transferred to all images involved. Finally the initial approximations for all unknown parameters are expressed in common system. The process concludes with the final bundle adjustment of all images. The described procedures have been programmed in the Matlab environment; codes available on the Internet have also been incorporated. The implemented algorithm has been applied to actual image sequences of various objects and evaluated against results from commercial software. Taking into account t certain inherent limitations of the algorithm implemented in this Thesis, its performance may be regarded as quite satisfactory.