In this thesis, estimation of motion from an image sequence is investigated. The emphasis is on the novel use of motion model for describing two dimensional motion. Special attention is directed towards general motion models which are not restricted to translational motion. In contrast to translational motion, the 2-D motion is described by the model using motion parameters. There are two major areas which can benefit from the study of general motion model. The first one is image sequence processing and compression. In this context, the use of motion model provides a more compact description of the motion information because the model can be applied to a larger area. The second area is computer vision. The general motion parameters provide clues to the understanding of the environment. This offers a simpler alternative to techniques such as optical flow analysis. A direct approach is adopted here to estimate the motion parameters directly from an image sequence. This has the advantage of avoiding the error caused by the estimation of optical flow. A differential method has been developed for the purpose. This is applied in conjunction with a multi-resolution scheme. An initial estimate is obtained by applying the algorithm to a low resolution image. The initial estimate is then refined by applying the algorithm to image of higher resolutions. In this way, even severe motion can be estimated with high resolution. However, the algorithm is unable to cope with the situation of multiple moving objects, mainly because of the least square estimator used. A second algorithm, inspired by the Hough transform, is therefore developed to estimate the motion parameters of multiple objects. By formulating the problem as an optimization problem, the Hough transform is computed only implicitly. This drastically reduces the computational requirement as compared with the Hough transform. The criterion used in optimization is a measure of the degree of match between two images. It has been shown that the measure is a well behaving function in the vicinity of the motion parameter vectors describing the motion of the objects, depending on the smoothness of the images. Therefore, smoothing an image has the effect of allowing longer range motion to be estimated. Segmentation of the image according to motion is achieved at the same time. The ability to estimate general motion in the situation of multiple moving objects represents a major step forward in 2-D motion estimation. Finally, the application of motion compensation to the problem of frame rate conversion is considered. The handling of the covered and uncovered background has been investigated. A new algorithm to obtain a pixel value for the pixels in those areas is introduced. Unlike published algorithms, the background is not assumed stationary. This presents a major obstacle which requires the study of occlusion in the image. During the research, the art of motion estimation hcis been advanced from simple motion vector estimation to a more descriptive level: The ability to point out that a certain area in an image is undergoing a zooming operation is one example. Only low level information such as image gradient and intensity function is used. In many different situations, problems are caused by the lack of higher level information. This seems to suggest that general motion estimation is much more than using a general motion model and developing an algorithm to estimate the parameters. To advance further the state of the art of general motion estimation, it is believed that future research effort should focus on higher level aspects of motion understanding.

In this thesis the concept behind our notion of video sculpture is to imagine an image sequence or movie as a three dimensional volume. We then also imagine that there is a frameset that traverses the image sequence to give us what we commonly think of as a video or movie. In the ordinary sense this frameset moves through an image sequence in a completely timeparallel linear fashion. In video sculpture, we free the frameset from these bounds so that we can sample space and time in completely unorthodox ways. We can view the whenwhere in previously unforeseen perspectives. Slices of the video environment can simultaneously reveal both past and future actions within a single frame. Building on this free representation of video spacetime, we then wrest the frame once more from the present constraints of topography and/or topology. The frame can bend and twist and jump and dive. The view of a fading quadratic surface cutting through two scenes makes for a beautiful curtain transition. We present a framework and an implementation for modeling the frame as it passes through the image sequence volume object.

As técnicas de super-resolução possibilitam combinar várias imagens de uma mesma cena para se obter uma imagem com resolução radiométrica e geométrica aumentada, denominada de imagem de super-resolução. Nessa imagem são realçadas características importantes possibilitando recuperar detalhes e informações. As aplicações envolvem diferentes áreas, tais como: na agricultura para identificar possíveis desmatamentos e controle de pragas, na área médica para a detecção de doenças em estágios iniciais, identificação facial de pessoas suspeitas em imagens de circuito fechado, reconstrução de filmes, identificação de placas de veículos, entre outras. No presente trabalho, é proposta uma metodologia para a geração de imagens de super-resolução a partir de uma região selecionada de um mosaico. Embora existam vários trabalhos publicados relacionados à geração de imagens de super-resolução, as metodologias não se aplicam para uma região específica do mosaico. E grande parte dos trabalhos utiliza uma imagem de referência, a partir da qual é gerada a imagem de super-resolução. Na metodologia proposta, inicialmente, é gerado um mosaico a partir de um conjunto de imagens baseando-se nos algoritmos SIFT ou SURF, BBF e RANSAC e é criada uma estrutura de dados, que organiza os pontos correlacionáveis das imagens com sobreposição, facilitando e simplificando o processo de fusão desses pontos para a obtenção da imagem de super-resolução. A ferramenta implementada a partir dessa metodologia, possibilita ao operador selecionar a região de interesse no mosaico, a partir da qual, é gerada a imagem de super-resolução utilizando as técnicas SIFT (ou SURF), interpolação Bicúbica e a fusão pelo valor mediano dos pontos da área com sobreposição das imagens da sequência. Para validar a metodologia, foram utilizados quatro conjuntos de imagens, que incluem imagens simuladas, obtidas com câmeras de baixa e alta resolução, imagens aéreas de áreas urbanas e rurais, coloridas e em escalas de cinza, e imagens contendo elementos textuais. Nas imagens simuladas foram adicionados ruídos e avaliada a imagem de super-resolução gerada por meio de duas métricas: raiz do erro médio quadrático (RMSE) e o índice de similaridade estrutural (SSIM). Os resultados mostraram que mesmo com valor de RMSE elevado, o SSIM foi acima de 70%, evidenciando o alto grau de similaridade. As imagens de super-resolução obtidas a partir de uma região dos mosaicos gerados foram comparadas com imagens superamostradas por meio de interpolações e avaliadas confrontando as imagens extrapoladas para verificação visual dos elementos da cena. Os resultados apresentados concluem que as imagens de super-resolução geradas, apresentam melhorias no que diz respeito à restauração das mesmas para futura análise de alvos de interesse, sem ter o retrabalho de adquirir novas imagens da cena, pois dependendo da cena analisada não será possível nova aquisição. O presente trabalho contribui com a geração de imagem de super-resolução, a partir de uma região do mosaico e com estruturas de dados e algoritmos que possibilitam a análise de regiões específicas do mosaico, sem que o mesmo tenha que ser processado integralmente. / Super-resolution techniques allow combining several images of the same scene in order to obtain an image with increased geometric and radiometric resolution, called super-resolution image. In this image are enhanced features allowing to recover important details and information. The applications involve different areas, such as: in the agriculture to identify possible deforestation and pest control, in the medical area to detect diseases in early stages, facial identification in images of suspects in closed loop, movies reconstruction, license plates recognition, among others. In this work, we propose a methodology for generating super-resolution images from a selected region of a mosaic. Although there are several published papers related to the generation of super-resolution images, the existing methodologies do not apply to a specific region of the mosaic. And the majority of studies use a reference image, from which is generated the super-resolution image. In the proposed methodology, initially, a mosaic is generated from a set of images based on the algorithms SIFT or SURF, BBF and RANSAC and creates a data structure that organizes the points correlate of the images with overlapping, facilitating and simplifying the fusion process of these points to obtain the super-resolution image. The tool implemented from this methodology allows to the operator to select the region of interest in the mosaic, from which is generated the image using super-resolution techniques SIFT (or SURF), Bicubic interpolation and fusion process by the median value of the points with overlapping area from the images of the sequence. In order to validate the methodology, we used four sets of images, including simulated images taken with cameras of low and high resolution, aerial images of urban and rural areas, color and grayscale images and images containing texts. In the simulated images were added noise and were evaluated the super-resolution image generated by two metrics: root mean square error (RMSE) and the structural similarity index (SSIM). The results showed that even with high RMSE value, the SSIM was above 70%, reflecting the high degree of similarity. The super-resolution images obtained from a region of the mosaics were compared with images generated by super-sampled interpolation and evaluated by comparing the images extrapolated to visual inspection of elements of the scene. From the results it can be concluded that the super-resolution images generated present improvements with regard to restoration of images for further analysis of targets of interest, without reworking to acquire new images of the scene, because depending on the analyzed scene it would not be possible a new acquisition. This work contributes to the generation of super-resolution image from a region of the mosaic and with data structures and algorithms which enable the analysis of specific regions of the mosaic without it has to be fully processed.

As técnicas de super-resolução possibilitam combinar várias imagens de uma mesma cena para se obter uma imagem com resolução radiométrica e geométrica aumentada, denominada de imagem de super-resolução. Nessa imagem são realçadas características importantes possibilitando recuperar detalhes e informações. As aplicações envolvem diferentes áreas, tais como: na agricultura para identificar possíveis desmatamentos e controle de pragas, na área médica para a detecção de doenças em estágios iniciais, identificação facial de pessoas suspeitas em imagens de circuito fechado, reconstrução de filmes, identificação de placas de veículos, entre outras. No presente trabalho, é proposta uma metodologia para a geração de imagens de super-resolução a partir de uma região selecionada de um mosaico. Embora existam vários trabalhos publicados relacionados à geração de imagens de super-resolução, as metodologias não se aplicam para uma região específica do mosaico. E grande parte dos trabalhos utiliza uma imagem de referência, a partir da qual é gerada a imagem de super-resolução. Na metodologia proposta, inicialmente, é gerado um mosaico a partir de um conjunto de imagens baseando-se nos algoritmos SIFT ou SURF, BBF e RANSAC e é criada uma estrutura de dados, que organiza os pontos correlacionáveis das imagens com sobreposição, facilitando e simplificando o processo de fusão desses pontos para a obtenção da imagem de super-resolução. A ferramenta implementada a partir dessa metodologia, possibilita ao operador selecionar a região de interesse no mosaico, a partir da qual, é gerada a imagem de super-resolução utilizando as técnicas SIFT (ou SURF), interpolação Bicúbica e a fusão pelo valor mediano dos pontos da área com sobreposição das imagens da sequência. Para validar a metodologia, foram utilizados quatro conjuntos de imagens, que incluem imagens simuladas, obtidas com câmeras de baixa e alta resolução, imagens aéreas de áreas urbanas e rurais, coloridas e em escalas de cinza, e imagens contendo elementos textuais. Nas imagens simuladas foram adicionados ruídos e avaliada a imagem de super-resolução gerada por meio de duas métricas: raiz do erro médio quadrático (RMSE) e o índice de similaridade estrutural (SSIM). Os resultados mostraram que mesmo com valor de RMSE elevado, o SSIM foi acima de 70%, evidenciando o alto grau de similaridade. As imagens de super-resolução obtidas a partir de uma região dos mosaicos gerados foram comparadas com imagens superamostradas por meio de interpolações e avaliadas confrontando as imagens extrapoladas para verificação visual dos elementos da cena. Os resultados apresentados concluem que as imagens de super-resolução geradas, apresentam melhorias no que diz respeito à restauração das mesmas para futura análise de alvos de interesse, sem ter o retrabalho de adquirir novas imagens da cena, pois dependendo da cena analisada não será possível nova aquisição. O presente trabalho contribui com a geração de imagem de super-resolução, a partir de uma região do mosaico e com estruturas de dados e algoritmos que possibilitam a análise de regiões específicas do mosaico, sem que o mesmo tenha que ser processado integralmente. / Super-resolution techniques allow combining several images of the same scene in order to obtain an image with increased geometric and radiometric resolution, called super-resolution image. In this image are enhanced features allowing to recover important details and information. The applications involve different areas, such as: in the agriculture to identify possible deforestation and pest control, in the medical area to detect diseases in early stages, facial identification in images of suspects in closed loop, movies reconstruction, license plates recognition, among others. In this work, we propose a methodology for generating super-resolution images from a selected region of a mosaic. Although there are several published papers related to the generation of super-resolution images, the existing methodologies do not apply to a specific region of the mosaic. And the majority of studies use a reference image, from which is generated the super-resolution image. In the proposed methodology, initially, a mosaic is generated from a set of images based on the algorithms SIFT or SURF, BBF and RANSAC and creates a data structure that organizes the points correlate of the images with overlapping, facilitating and simplifying the fusion process of these points to obtain the super-resolution image. The tool implemented from this methodology allows to the operator to select the region of interest in the mosaic, from which is generated the image using super-resolution techniques SIFT (or SURF), Bicubic interpolation and fusion process by the median value of the points with overlapping area from the images of the sequence. In order to validate the methodology, we used four sets of images, including simulated images taken with cameras of low and high resolution, aerial images of urban and rural areas, color and grayscale images and images containing texts. In the simulated images were added noise and were evaluated the super-resolution image generated by two metrics: root mean square error (RMSE) and the structural similarity index (SSIM). The results showed that even with high RMSE value, the SSIM was above 70%, reflecting the high degree of similarity. The super-resolution images obtained from a region of the mosaics were compared with images generated by super-sampled interpolation and evaluated by comparing the images extrapolated to visual inspection of elements of the scene. From the results it can be concluded that the super-resolution images generated present improvements with regard to restoration of images for further analysis of targets of interest, without reworking to acquire new images of the scene, because depending on the analyzed scene it would not be possible a new acquisition. This work contributes to the generation of super-resolution image from a region of the mosaic and with data structures and algorithms which enable the analysis of specific regions of the mosaic without it has to be fully processed.

We describe a new direct method for estimating structure and motion from image intensities of multiple views. We extend the direct methods of Horn- and-Weldon to three views. Adding the third view enables us to solve for motion, and compute a dense depth map of the scene, directly from image spatio -temporal derivatives in a linear manner without first having to find point correspondences or compute optical flow. We describe the advantages and limitations of this method which are then verified through simulation and experiments with real images.

Photogrammetrische Methoden gewinnen zunehmend an Bedeutung im bau­tech­nischen Versuchswesen. Die Auswertung von Bildsequenzen ermöglicht eine kontakt­lose, flächenhafte, hochaufgelöste und hochgenaue Veränderungs­detek­tion von Ober­flächen in der Materialprüfung und Bauwerksüberwachung. Diese Arbeit behan­delt einige Aspekte der Deformationsanalyse auf Basis von Bild­sequenzen mit Hilfe triangulierter Verschiebungsfelder. Zunächst wird auf Unter­suchungen zu Defor­ma­tionen ebener Objektoberflächen, die mit mono­kularen Bild­sequenzen beo­bachtet wurden, eingegangen. Im weiteren Verlauf wird auf Stereobildsequenzen über­ge­gangen, die Deformations­mes­sungen für beliebige Ober­flächen erlauben. Im ersten Teil der Arbeit wird gezeigt, wie Verschiebungsfelder in monokularen Bild­sequenzen bestimmt werden können. Die Bildpunkte, an welche die Verschie­bungen geknüpft sind, werden zu einem Dreiecksnetz trianguliert. Jedes einzelne Dreieck wird auf Änderungen zu der Referenzepoche, die als die erste Epoche ohne jegliche Defor­mation definiert ist, untersucht. Ein gängiges Verfahren zur Analyse solcher Verän­derungen ist die Berechnung von Haupt­dehnungen für jedes Dreieck. Schwell­werte können zur Erkennung deformierter Bereiche und die farbkodierte Darstellung der Hauptdehnungen für eine visuelle Betrachtung genutzt werden. In den räumlich verteilten Hauptdehnungen sowie im zeitlichen Ablauf treten Rausch­effekte auf. Deshalb werden verschiedene Filtermethoden zur Rausch­unter­drückung untersucht. Dabei kommt ein Filter zum Einsatz, der gleichzeitig in der räumlichen sowie der zeitlichen Dimension filtert. Es werden aber auch Filter unter­sucht, die in beiden Dimensionen getrennt filtern. Aus den Hauptdehnungen können nicht direkt Rissbreiten abgeleitet werden. Diese spielen für die Materialprüfung im Bauwesen allerdings eine wichtige Rolle, wes­wegen sich diese Arbeit auch mit der Berechnung von Riss­breiten in Dreiecks­netzen befasst. Als deformierte Dreiecke werden diejenigen detektiert, deren Hauptdehnung einen Schwellwert überschreiten. Für diese Kandidaten werden im Folgenden Rissbreiten bestimmt. Drei verschiedene Verfahren für die Ermittlung von Rissbreiten werden vorgestellt und verglichen. Die Dehnbarkeit faserbewehrter Komposite, die unter anderem zur Verstärkung von Mauern und anderen Bauwerken verwendet werden, wird bei Belastung durch die Bildung multipler Rissstrukturen gewährleistet. Auf Grund dessen widmet sich ein weiterer Teil der Dissertation der Auswertung multipler Riss­strukturen. Hierzu werden dichte Verschiebungsfelder berechnet. Dann wird zunächst eine Auswahl der verfolgten Punkte genutzt, um ein grobes Dreiecks­netz zu generieren. Deformierte Dreiecke der ausgedünnten triangu­lierten Punktmenge werden mit dem Betrag des relativen Trans­lations­vektors, der als Deformations­maß eingeführt wird, detektiert. Eine iterative Verdichtung des Dreiecknetzes in defor­mierten Bereichen ermöglicht die Auswertung enger Riss­muster. Zudem erlaubt eine Ausgleichung, dass nicht-triangulierte Punkte des dichten Verschie­bungs­feldes in die Rissbreiten­berechnung einbe­zogen werden können. Ein weiterer Bestandteil der Arbeit ist die Betrachtung unebener Oberflächen, die mit Stereokamerasystemen beobachtet werden. Dazu werden die Algorithmen für die zweidimensionale Auswertung entsprechend übertragen und erweitert. Auf Basis von Verschiebungsfeldern dreidimensionaler Punkte wird auch hier ein Dreiecksnetz zur Änderungsdetektion genutzt. So wird am Beispiel von dynamischen Dehnungstests an zylindrischen Probe­körpern ein Algorithmus zur Rissbreitenmessung auf nicht ebenen Ober­flächen vorge­stellt. Dabei wird angenommen, dass die Defor­mationen ausschließlich tangential zur Oberfläche auftreten. Dies erlaubt die Transformation (Kongruenz­abbildung) der Dreiecke in einen zwei­dimen­sionalen Raum und auch eine zwei­dimensionale Auswertung. Außerdem wird eine Methode zur Berechnung des dreidimensionalen Riss­öffnungs­vektors präsentiert. Dieses Verfahren ist eine Erweiterung zum vorher­gehenden Algorithmus und erlaubt zudem die Vermessung vertikaler Defor­ma­tionen. Defor­mierte Dreiecke im trian­gulierten dreidimensionalen Verschie­bungs­feld werden mit Hilfe des zwei­dimen­sionalen Relativ­translations­vektor­betrags der in den zwei­dimen­sionalen Raum transformierten Dreiecke detek­tiert. Anschließend folgt für alle defor­mierten Dreiecke durch Hinzunahme min­des­tens eines undeformierten Nachbar­dreiecks die Berechnung eines drei­dimen­sionalen relativen Trans­lations­vektors, mit Hilfe dessen die Komponenten des Riss­öffnungsvektors ermittelt werden.:Kurzfassung iii Abstract v 1. Einführung 1 1.1. Struktur der Arbeit 1 1.2. Motivation 2 1.3. Verwandte Arbeiten 4 1.4. Ziele der Arbeit 7 2. Photogrammetrische Deformationsmessung in monokularen Bildsequenzen 8 2.1. Filtermethoden in Dreiecksnetzen 9 2.2. Rissbreitenberechnung mit Hilfe von Dreiecksnetzen 19 2.3. Strategie zur Rissbreitenmessung für multiple Rissstrukturen 29 3. Photogrammetrische Deformationsmessung in Stereobildsequenzen 50 3.1. Rissbreitenberechnung für tangentiale Deformationen auf nicht ebenen Oberflächen mit gegebenem 3D-Verschiebungsfeld 51 3.2. Berechnung des dreidimensionalen Rissöffnungsvektors bei gegebenem 3D-Verschiebungsfeld 59 4. Diskussion 70 5. Ausblick 77 5.1. Bestimmung der Anzahl der Risse 77 5.2. Rissspitzenbestimmung und -verfolgung 78 5.3. Anwendung der entwickelten Algorithmen auf Voxeldaten 78 5.4. Modellerweiterung durch Relativrotation 82 5.5. Genauigkeitssteigerungen für die Rissposition 82 5.6 Verbesserung der Rissnormalenschätzung 82 Literaturverzeichnis 83 Abkürzungsverzeichnis 89 Tabellenverzeichnis 90 Abbildungsverzeichnis 90 / Photogrammetric methods are gaining importance in civil engineering material testing and structural health monitoring. The analysis of image sequences ensures an extensive change detection of surfaces with a high spatial resolution and a high accuracy. This thesis deals with some aspects of deformation analysis based on image sequences and triangulated displacement fields. At the beginning, the examination of planar surfaces of specimens observed with monocular image sequences is considered. Later, a transition to stereo image sequences is given because they allow a deformation measurement of arbitrary surfaces. The first part of the thesis shows how to derive displacement fields from monocular image sequences. The matching points corresponding to the displace­ments are triangulated into a mesh. Each triangle is compared to the reference epoch which is defined as the first time epoch under zero load without any deformation. As a current method, principal strains are used to detect deformations. Thresholds can be used to find deformed areas. In addition, color-coded maps of the principal strains are helpful for a visual detection. In the field of the principal strains, noise effects appear in the spatial as well as in the temporal domain. Therefore, different filter methods are applied to reduce noise. In addition to filter techniques that are applied independently in the time and the spatial domain, a combined spatio-temporal filter is tested. Crack widths cannot be derived directly from principal strains but crack widths are an important issue in civil engineering material testing. For this reason, this thesis also gives attention to the computation of crack widths in triangle meshes. The principal strains of the triangles are tested for exceeding a threshold to detect deformed triangles. For the deformed triangles, crack widths are computed. Three different methods for the crack width determination are presented and compared. Multiple cracking ensures the ductility of loaded fiber-reinforced composites used to strengthen walls among other things. Therefore, another part of the dissertation deals with the photogrammetric analysis of multiple crack patterns. Herein, dense displacement fields are computed. Then, a thinned-out set of points is triangulated into a mesh. For each triangle, the norm of the relative translations vector defined as a new quantity to detect deformations is deter­mined and used to find cracked triangles. The mesh is densified iteratively in deformed areas to ensure an analysis of narrow crack structures. In addition, a least squares algorithm is presented which allows that points of the displace­ment field, that are not part of the mesh, can be included in the crack width computation. A further part of the dissertation deals with non-planar surfaces observed with stereo camera systems. The algorithms of the two dimensional analysis are adapted and extended to use them for these applications. These methods are based on three dimensional displacement fields and also use triangle meshes to detect deformed areas. One algorithm concentrates on the crack width measurement of non-planar surfaces with deformations that are only tangential to the surface. The method is applied on a cylindrical specimen in a dynamic tension test. The assumption that deformations are tangential to the surface allows the transformation of the triangles in the two dimensional space and also a two dimensional analysis. In addition, an algorithm for the computation of the three dimensional crack opening vectors is presented. This method is an extension to the foregoing algorithm and is capable of measuring vertical deformations. To find deformed triangles in the triangulated three dimensional displacement field, the triangles are transformed in the two dimensional space in a first step. In a second step, the norm of the two dimensional relative translation vector is determined and tested if it exceeds a threshold. In the following, for each deformed triangle, the three dimensional relative translation vector is computed using a undeformed neighbor triangle. At the end, the three dimensional relative translation vectors can be transformed to the crack opening vectors.:Kurzfassung iii Abstract v 1. Einführung 1 1.1. Struktur der Arbeit 1 1.2. Motivation 2 1.3. Verwandte Arbeiten 4 1.4. Ziele der Arbeit 7 2. Photogrammetrische Deformationsmessung in monokularen Bildsequenzen 8 2.1. Filtermethoden in Dreiecksnetzen 9 2.2. Rissbreitenberechnung mit Hilfe von Dreiecksnetzen 19 2.3. Strategie zur Rissbreitenmessung für multiple Rissstrukturen 29 3. Photogrammetrische Deformationsmessung in Stereobildsequenzen 50 3.1. Rissbreitenberechnung für tangentiale Deformationen auf nicht ebenen Oberflächen mit gegebenem 3D-Verschiebungsfeld 51 3.2. Berechnung des dreidimensionalen Rissöffnungsvektors bei gegebenem 3D-Verschiebungsfeld 59 4. Diskussion 70 5. Ausblick 77 5.1. Bestimmung der Anzahl der Risse 77 5.2. Rissspitzenbestimmung und -verfolgung 78 5.3. Anwendung der entwickelten Algorithmen auf Voxeldaten 78 5.4. Modellerweiterung durch Relativrotation 82 5.5. Genauigkeitssteigerungen für die Rissposition 82 5.6 Verbesserung der Rissnormalenschätzung 82 Literaturverzeichnis 83 Abkürzungsverzeichnis 89 Tabellenverzeichnis 90 Abbildungsverzeichnis 90

This work investigates the process of automating reconstruction of buildings from video imagery. New metrics were developed to detect the least blurred images in a sequence for further processing. Phase correlation for point matching was investigated and new metrics were developed to identify successful matches. Direct relative orientation algorithms were investigated in-depth. A significant finding was a new 6-point algorithm which outperformed previously published algorithms for a number of calibrated camera and target geometries. The development of the new metrics and the outcomes from the comprehensive investigations conducted have contributed to a better understanding of the challenging problem of automatically reconstructing 3D objects from image sequences.

No description available.

This master´s thesis deals with methods for synthesis of digital image sequence with moving object. At first, we describe basic concepts from Fourier analysis and statistics that are essential for understanding the issue and afterwards we describe methods for the synthesis that were tested on a series of images of a comet moving on a background of a night sky. Finally, we compare the methods and analyse the outcomes.

No description available.