This dissertation describes the design and implementation of a system that has been designed to extract 3D information from pairs of 2D images. System input consists of two images taken by an ordinary digital camera. System output is a full 3D model extracted from 2D images. There are no assumptions about the positions of the cameras during the time when the images are being taken, but the scene must not undergo any modifications. The process of extracting 3D information from 2D images consists of three basic steps. First, point matching is performed. The main contribution of this step is the introduction of an approach to matching image segments in the context of an approximation space. The second step copes with the problem of estimating external camera parameters. The proposed solution to this problem uses 3D geometry rather than the fundamental matrix widely used in 2D to 3D conversion. In the proposed approach (DirectGS), the distances between reprojected rays for all image points are minimised. The contribution of the approach considered in this step is a definition of an optimal search space for solving the 2D to 3D conversion problem and introduction of an efficient algorithm that minimises reprojection error. In the third step, the problem of dense matching is considered. The contribution of this step is the introduction of a proposed approach to dense matching of 3D object structures that utilises the presence of points on lines in 3D space. The theory and experiments developed for this dissertation demonstrate the usefulness of the proposed system in the process of digitizing 3D information. The main advantage of the proposed approach is its low cost, simplicity in use for an untrained user and the high precision of reconstructed objects. / October 2007

This dissertation describes the design and implementation of a system that has been designed to extract 3D information from pairs of 2D images. System input consists of two images taken by an ordinary digital camera. System output is a full 3D model extracted from 2D images. There are no assumptions about the positions of the cameras during the time when the images are being taken, but the scene must not undergo any modifications. The process of extracting 3D information from 2D images consists of three basic steps. First, point matching is performed. The main contribution of this step is the introduction of an approach to matching image segments in the context of an approximation space. The second step copes with the problem of estimating external camera parameters. The proposed solution to this problem uses 3D geometry rather than the fundamental matrix widely used in 2D to 3D conversion. In the proposed approach (DirectGS), the distances between reprojected rays for all image points are minimised. The contribution of the approach considered in this step is a definition of an optimal search space for solving the 2D to 3D conversion problem and introduction of an efficient algorithm that minimises reprojection error. In the third step, the problem of dense matching is considered. The contribution of this step is the introduction of a proposed approach to dense matching of 3D object structures that utilises the presence of points on lines in 3D space. The theory and experiments developed for this dissertation demonstrate the usefulness of the proposed system in the process of digitizing 3D information. The main advantage of the proposed approach is its low cost, simplicity in use for an untrained user and the high precision of reconstructed objects.

We propose algorithms for organization of images in wide-area sparse-view datasets. In such datasets, if the images overlap in scene content, they are related by wide-baseline geometric transformations. The challenge is to identify these relations even if the images sparingly overlap in their content. The images in a dataset are then grouped into sets of related images with the relations captured in each set as a basal (minimal and foundational) graph structures. Images form the vertices in the graph structure and the edges define the geometric relations between the images. We use these basal graphs for geometric walkthroughs and detection of noisy location (GPS) and orientation (magnetometer) information that may be stored with each image. We have five algorithmic contributions. First, we propose an algorithm BLOGS (Balanced Local and Global Search) that uses a novel hybrid Markov Chain Monte Carlo (MCMC) strategy called 'hop-diffusion' for epipolar geometry estimation between a pair of wide-baseline images that is 10 times faster and more accurate than the state-of-the-art. Hops are global searches and diffusions are local searches. BLOGS is able to handle very wide-baseline views characteristic of wide-area sparse-view datasets. It also produces a geometric match score between an image pair. Second, we propose a photometric match score, the Cumulative Correspondence Score (CCS). The proposed photometric scores are fast approximations of the computationally expensive geometric scores. Third, we use the photometric scores and the geometric scores to find groups of related images and to organize them in the form of basal graph structures using a novel hybrid algorithm we call theCOnnected component DIscovery by Minimally Specifying an Expensive Graph (CODIMSEG). The objective of the algorithm is to minimize the number of geometric estimations and yield results similar to what would be achieved if all-pair geometric matching were done. We compared the performances of the CCS and CODIMSEG algorithms with GIST (means summary of an image) and k-Nearest Neighbor (k-NN) based approaches. We found that CCS and CODIMSEG perform significantly better than GIST and k-NN respectively in identifying visually connected images. Our algorithm achieved more than 95% true positive rate at 0% false positive rate. Fourth, we propose a basal tree graph expansion algorithm to make the basal graphs denser for applications like geometric walk-throughs using the minimum Hamiltonian path algorithm and detection of noisy position (GPS) and orientation (magnetometer) tags. We propose two versions of geometric walkthroughs, one using minimum spanning tree based approximation of the minimum Hamiltonian path on the basal tree graphs and other using the Lin-Kernighan heuristic approximation on the expanded basal graph. Conversion of a non-linear tree structure to a linear path structure leads to discontinuities in path. The Lin-Kernighan algorithm on the expanded basal graphs is shown to be a better approach. Fifth, we propose a vision based geometric voting algorithm to detect noisy GPS and magnetometer tags using the basal graphs. This problem has never been addressed before to the best of our knowledge. We performed our experiments on the Nokia dataset (which has 243 images in the 'Lausanne' dataset and 105 images in the 'Demoset'), ArtQuad dataset (6514 images) and Oxford dataset (5063 images). All the three datasets are very different. Nokia dataset is a very wide-baseline sparse-view dataset. ArtQuad dataset is a wide-baseline dataset with denser views compared to the Nokia dataset. Both these datasets have GPS tagged images. Nokia dataset has magnetometer tags too. ArtQuad dataset has 348 images with the commercial GPS information as well as high precision differential GPS data which serves as ground truth for our noisy tag detection algorithm. Oxford dataset is a wide-baseline dataset with plenty of distracters that test the algorithm's capability to group images correctly. The larger datasets test the scalability of our algorithms. Visually inspected feature matches and image matches were used as ground truth in our experiments. All the experiments were done on a single PC.

This dissertation describes the design and implementation of a system that has been designed to extract 3D information from pairs of 2D images. System input consists of two images taken by an ordinary digital camera. System output is a full 3D model extracted from 2D images. There are no assumptions about the positions of the cameras during the time when the images are being taken, but the scene must not undergo any modifications. The process of extracting 3D information from 2D images consists of three basic steps. First, point matching is performed. The main contribution of this step is the introduction of an approach to matching image segments in the context of an approximation space. The second step copes with the problem of estimating external camera parameters. The proposed solution to this problem uses 3D geometry rather than the fundamental matrix widely used in 2D to 3D conversion. In the proposed approach (DirectGS), the distances between reprojected rays for all image points are minimised. The contribution of the approach considered in this step is a definition of an optimal search space for solving the 2D to 3D conversion problem and introduction of an efficient algorithm that minimises reprojection error. In the third step, the problem of dense matching is considered. The contribution of this step is the introduction of a proposed approach to dense matching of 3D object structures that utilises the presence of points on lines in 3D space. The theory and experiments developed for this dissertation demonstrate the usefulness of the proposed system in the process of digitizing 3D information. The main advantage of the proposed approach is its low cost, simplicity in use for an untrained user and the high precision of reconstructed objects.

This thesis is dedicated photogrammetric image analysis that makes it possible from your photos with the help selected methods to determine the location and dimensions of objects recorded on them. There are explained the basics of photogrammetry and its current application. Chapters focused on digital imaging describing its characteristics, treatment options and key points findability for the scene calibration. For a comprehensive view are in this thesis introduced examples of existing software, its possibilities and use in practice.

The problem of epipolar geometry estimation together with correspondence establishment in case of wide baseline and large scale changes and rotation has been addressed in this work. This work deals with cases that are heavily noised by outliers. The jump diffusion MCMC method has been employed to search for the non-degenerate epipolar geometry with the highest probabilistic support of putative correspondences. At the same time, inliers in the putative set are also identified. The jump steps involve large movements guided by a distribution of similarity based priors while diffusion steps are small movements guided by a distribution of likelihoods given by the Joint Feature Distribution (JFD). The 'best so far' samples are accepted in accordance to Metropolis-Hastings method. The diffusion steps are carried out by sampling conditioned on the 'best so far', making it local to the 'best so far' sample, while jump steps remain unconditioned and span across the correspondence and motion space according to a similarity based proposal distribution making large movements. We advance the theory in three novel ways. First, a similarity based prior proposal distribution which guide jump steps. Second, JFD based likelihoods which guide diffusion steps allowing more focused correspondence establishment while searching for epipolar geometry. Third, a measure of degeneracy that allows to rule out degenerate configurations. The jump diffusion framework thus defined allows handling over 90% outliers even in cases where the number of inliers is very few. Practically, the advancement lies in higher precision and accuracy that has been detailed in this work by comparisons. In this work, BLOGS is compared with LO-RANSAC, NAPSAC, MAPSAC and BEEM algorithm, which are the current state of the art competing methods, on a dataset that has significantly more change in baseline, rotation, and scale than those used in the state of the art. Performance of these algorithms and BLOGS are quantitatively benchmark for a comparison by estimating the error in the epipolar geometry given by root mean Sampson's distance from manually specified corresponding point pairs which serve as a ground truth. Not just is BLOGS able to tolerate very high outlier rates, but also gives result of similar quality in 10 times lesser number of iterations than the most competitive among the compared algorithms.

No description available.

No / An algorithm for the rectification of uncalibrated images is presented and applied to a variety of cases. The algorithm generates the rectifying transformations directly from the geometrical relationship between the images, using any three correspondences in the images to define a reference plane. A small set of correspondences is used to calculate an initial rectification. Additional correspondences are introduced semi-automatically, by correlating regions of the rectified images. Since the rectified images of surfaces in the reference plane have no relative distortion, features can be matched very accurately by correlation, allowing small changes in disparity to be detected. In the 3-d reconstruction of an architectural scene, differences in depth are resolved to about 0.001 of the distance from camera to subject.

In this thesis, opti-acoustic stereo imaging, which is the deployment of two-dimensional (2D) high frequency imaging sonar with the electro-optical camera in calibrated stereo configuration, is studied. Optical cameras give detailed images in clear waters. However, in dark or turbid waters, information coming from electro-optical sensor is insufficient for accurate scene perception. Imaging sonars, also known as acoustic cameras, can provide enhanced target details under these scenarios. To illustrate these visibility conditions, a 2D high frequency imaging sonar simulator as well as an underwater optical image simulator is developed. A computationally efficient algorithm is also proposed for the post-processing of the returned sonar signals. Where optical visibility allows, integration of the sonar and optical images effectively provides binocular stereo vision capability and enables the recovery of three-dimensional (3D) structural information. This requires solving the feature correspondence problem for these completely different sensing modalities. Geometrical interpretation of this problem is examined on the simulated optical and sonar images. Matching the features manually, 3D reconstruction performance of opti-acoustic system is also investigated. In addition, motion estimation from opti-acoustic image sequences is studied. Finally, a method is proposed to improve the degraded optical images with the help of sonar images. First, a nonlinear mapping is found to match local the features in opti-acoustical images. Next, features in the sonar image is mapped to the optical image using the transformation. Performance of the mapping is evaluated for different scene geometries.

Ένας από τους παράγοντες που ενοχοποιούνται για την ανάπτυξη ινομυϊκής υπερπλασίας στη φλεβική αναστόμωση των συνθετικών αρτηριοφλεβικών μοσχευμάτων, είναι η διαταραχή των αιμοδυναμικών συνθηκών στην περιοχή της αναστόμωσης. Για τον υπολογισμό της ροής, δηλαδή των πεδίων ταχύτητας, διατμητικής τάσης και στροβιλισμού, στην περιοχή αυτή, χρησιμοποιούνται μέθοδοι της υπολογιστικής δυναμικής των ρευστών, οι οποίες προϋποθέτουν γνώση της τριδιάστατης γεωμετρίας των αγγείων και του μοσχεύματος. Στην παρούσα διπλωματική εργασία αναπτύσσεται μια μεθοδολογία και ο αντίστοιχος αλγόριθμος για τον προσδιορισμό της τριδιάστατης γεωμετρίας της κεντρικής γραμμής των αγγείων από διεπίπεδη αγγειογραφία, όπου η σχέση των δύο συστημάτων αναφοράς θεωρείται άγνωστη, καθώς και για τη σχεδίαση κυκλικών διατομών σε επιλεγμένες θέσεις για την προσέγγιση του αγγειακού αυλού. Η μέθοδος βασίζεται στην θεωρία των Metz – Fencil (1989) και απαιτεί την εκ των προτέρων γνώση δύο ζευγών αντίστοιχων σημείων στις προβολές για τον προσδιορισμό της σχέσης που συνδέει τα δύο συστήματα αναφοράς. Για την αναγνώριση αντίστοιχων σημείων στις προβολές χρησιμοποιείται η τεχνική της επιπολικής γραμμής, ενώ η ανακατασκευή της κεντρικής γραμμής πραγματοποιείται με χρήση παραμετρικής φυσικής spline. Πραγματοποιήθηκε έλεγχος της μεθόδου με χρήση πρότυπης γεωμετρίας και διαπιστώθηκε ότι η ακρίβεια της ανακατασκευής εξαρτάται από το πλήθος και την ποιότητα των σημείων ελέγχου της spline. Τελικά, η μέθοδος εφαρμόστηκε σε πρότυπο αντικείμενο, γνωστής γεωμετρίας, ανάλογης αυτής που λαμβάνεται σε πραγματικές αγγειογραφικές προβολές αρτηριοφλεβικής αναστόμωσης στην περιοχή της καρωτίδας και διαπιστώθηκε ότι ανακατασκευάζει με καλή ακρίβεια την κεντρική γραμμή του αντικειμένου. / One of the factors that have been incriminated for the growth of fibromuscular hyperplasia at the anastomosis of the synthetic arteriovenous implant, is the disturbance of the hemodynamic conditions at the region of the anastomosis. For the computation of the flow at this region, that is the fields of velocity, shear stress and rotation, methods of computational flow dynamics are used, which require that the 3D geometry of the vessels and the implant are known in advance. In this thesis, we developed a methodology and the respective algorithm for the determination of the 3D geometry of the central line of the vessels from biplane angiography, for which the relation of the two systems of coordinates are unknown, as well as for the drawing of circular cross section at selected positions for approximation of arterial lumen. The method is based on the theory of C.E.Metz and L.E.Fencil (1989) and requires the knowledge of two pairs of respective points on the views in advanced in order to calculate the rotation matrix and the translation vector that relate the two systems of coordinates. For recognition of respective points on the two views the epipolar line technique is being used, while the central line is reconstructed using a parametric natural spline. The method was tested using a model and it showed that the accuracy of the reconstruction depends on the number and the quality of the control points of the spline. Finally, the method was implemented on a model object with geometry, analogous to that we get from real angiographic views of arteriovenous anastomosis at the region of the carotid artery, and its central line was reconstructed with very good accuracy.