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In scientific data visualization huge amounts of data are generated, which implies the task of analyzing these in an efficient way. This includes the reliable detection of important parts and a low expenditure of time and effort. This is especially important for the big-sized seismic volume datasets, that are required for the exploration of oil and gas deposits. Since the generated data is complex and a manual analysis is very time-intensive, a semi-automatic approach could on one hand reduce the time required for the analysis and on the other hand offer more flexibility, than a fully automatic approach.
This master's thesis introduces an algorithm, which is capable of locating regions of interest in seismic volume data automatically by detecting anomalies in local histograms. Furthermore the results are visualized and a variety of tools for the exploration and interpretation of the detected regions are developed. The approach is evaluated by experiments with synthetic data and in interviews with domain experts on the basis of real-world data. Conclusively further improvements to integrate the algorithm into the seismic interpretation workflow are suggested.
This work represents a quantitative analysis and visualisation of scar tissue of the left ventricular myocard. The scar information is shown in the late enhancement data, that highlights the avitale tissue with the help of a contrast agent. Through automatic methods, the scar is extracted from the image data and quantifies the size, location and transmurality. The transmurality shows a local measurement between the heart wall und the width of the scar. The developed methods help the cardiologist to analyse the measurement, the reason and the degree of the heart failure in a short time period. He can further control the results by several visual presentations. The deformation of the scar tissue over the heart cycle is implemented in another scientific work. A visual improvement of the deformation result which extracts the scar out of the data is aspired. The avital tissue is shown in a more comfortable way by eliminating the unnecessary image information and therefore improves the visual analysis of the pumping heart. Both methods show a detailed analysis of the scar tissue. This supports the clinic practical throughout the manual analysis.
This thesis deals with the development of an authoring system for modeling 3D environments with physical description. In contrast to creating scenes in other common modeling tools, one can now compute and describe physical entities of a scene additional to the usual geometry. It is very important for those authoring systems to be extendable and customizable for specific requirement of the user. The focus lies on developing simple program architecture, which is easy to extend and to modify.
Die Herzkranzgefäße sind verantwortlich für die Blutversorgung des Herzmuskels. Eine Störung des Blutflusses durch Verengungen oder gar Verstopfungen dieser Gefäße kann Herzerkrankungen bis hin zum Herzinfarkt auslösen. Eine Analyse dieser Strukturen ist damit von vitalem Interesse für die Diagnostik solcher Erkrankungen als auch die Planung einer möglichen Therapie. Im Rahmen dieser Diplomarbeit soll ein Verfahren entwickelt und implementiert werden, das es ermöglicht, einzelne Projektionsbilder aus der Angiographie mit tomographischen Volumendaten (CT, MR) in Deckung zu bringen, d.h. zu matchen. Die Fragestellung dahinter ist die nach der Korrelation der aus den Volumendaten gewonnenen Informationen über die Herzkranzgefäße mit dem gegenwärtigen "Gold-Standard" - der Angiographie. Dazu notwendig ist die Entwicklung eines Ansatzes zur Generierung von, den Angiographiebildern entsprechenden, künstlichen Projektionsbildern aus den (bereits segmentierten) Volumendaten. Die Festlegung der Projektionsparameter sowie das Matching selbst sollen automatisch erfolgen.
For definite isolation and classification of important features in 3D multi-attribute volume data, multidimensional transfer functions are inalienable. Yet, when using multiple dimensions, the comprehension of the data and the interaction with it become a challenge. That- because neither the control of the versatile input parameters nor the visualization in a higher dimensional space are straightforward.
The goal of this thesis is the implementation of a transfer function editor which supports the creation of a multidimensional transfer function. Therefore different visualization and interaction techniques, like Parallel Coordinates, are used. Furthermore it will be possible to choose and combine the used dimensions interactively and the rendered volume will be adapted to the user interaction in real time.
Der Zwang zur Entwicklung immer neuer Technologien hat den Entwicklungsaufwand vieler Spiele enorm in die Höhe getriebenen. Aufwändigere Grafiken und Spiele-Engines erfordern mehr Künstler, Grafiker, Designer und Programmierer, weshalb die Teams immer größer werden. Bereits jetzt liegt die Entwicklungszeit für einen Ego-Shooter bei über 3 Jahren, und es entstehen Kosten bis in den zweistelligen Millionenbereich. Neue Techniken, die entwickelt werden sollen, müssen daher nach Aufwand und Nutzen gegeneinander abgewogen werden. In dieser Arbeit soll daher eine echtzeitfähige Lösung entwickelt werden, die genaue und natürlich aussehende Animationen zur Visualisierung von Charakter-Objekt-Interaktionen dynamisch mithilfe von Inverser Kinematik erstellt. Gleichzeitig soll der Aufwand, der für die Nutzung anfällt, minimiert werden, um möglichst geringe zusätzliche Entwicklungskosten zu generieren.
Research has shown that people recognize personality, gender, inner states and many other items of information by simply observing human motion. Therefore the expressive human motion seems to be a valuable non-verbal communication channel. On the quest for more believable characters in virtual three dimensional simulations a great amount of visual realism has been achieved during the last decades. However, while interacting with synthetic characters in real-time simulations, often human users still sense an unnatural stiffness. This disturbance in believability is generally caused by a lack of human behavior simulation. Expressive motions, which convey personality and emotional states can be of great help to create more plausible and life-like characters. This thesis explores the feasibility of an automatic generation of emotionally expressive animations from given neutral character motions. Such research is required since common animation methods, such as manual modeling or motion capturing techniques, are too costly to create all possible variations of motions needed for interactive character behavior. To investigate how emotions influence human motion relevant literature from various research fields has been viewed and certain motion rules and features have been extracted. These movement domains were validated in a motion analysis and implemented in a system in an exemplary manner capable of automating the expression of angry, sad and happy states in a virtual character through its body language. Finally, the results were evaluated in user test.
Die Arbeit befasst sich mit der Thematik "Frauen und Computerspiele". Um einen kurzen Überblick über die Thematik zu geben, werden zunächst einige aktuelle Studien präsentiert. Anschließend werden bisherige Erkenntnisse zu den Vorlieben weiblicher Computerspieler herausgestellt. Insbesondere wird untersucht, was Frauen motiviert, Computerspiele zu spielen, welche Themen und Konfliktlösungen sie bevorzugen. Auch die Zugangsweise zum Computer wird betrachtet und die Frage, wie hoch die Fehlertoleranz von Frauen bei Computerspielen ist. Um die Präferenzen weiblicher Spieler untersuchen zu können, wird ein Casual Game mit zwei unterschiedlichen Leveln entwickelt. Das erste ähnelt vom Aufbau her Casual Games, die aktuell im Internet zu finden sind und schon einige Frauen begeistert haben, z.B. "Cake Mania". In das Spiel, insbesondere in das zweite Level, sind zusätzliche Elemente eingebaut, welche den ausgearbeiteten Vorlieben entsprechen. Abschließend wird das Spiel weiblichen Testpersonen über das Internet zur Verfügung gestellt, und über einen Online-Fragebogen werden die herausgearbeiteten Thesen überprüft.
Statistical Shape Models (SSMs) are one of the most successful tools in 3Dimage analysis and especially medical image segmentation. By modeling the variability of a population of training shapes, the statistical information inherent in such data are used for automatic interpretation of new images. However, building a high-quality SSM requires manually generated ground truth data from clinical experts. Unfortunately, the acquisition of such data is a time-consuming, error-prone and subjective process. Due to this effort, the majority of SSMs is often based on a limited set of this ground truth training data, which makes the models less statistically meaningful. On the other hand, image data itself is abundant in clinics from daily routine. In this work, methods for automatically constructing a reliable SSM without the need of manual image interpretation from experts are proposed. Thus, the training data is assumed to be the result of any segmentation algorithm or may originate from other sources, e.g. non-expert manual delineations. Depending on the algorithm, the output segmentations will contain errors to a higher or lower degree. In order to account for these errors, areas of low probability of being a boundary should be excluded from the training of the SSM. Therefore, the probabilities are estimated with the help of image-based approaches. By including many shape variations, the corrupted parts can be statistically reconstructed. Two approaches for reconstruction are proposed - an Imputation method and Weighted Robust Principal Component Analysis (WRPCA). This allows the inclusion of many data sets from clinical routine, covering a lot more variations of shape examples. To assess the quality of the models, which are robust against erroneous training shapes, an evaluation compares the generalization and specificity ability to a model build from ground truth data. The results show, that especially WRPCA is a powerful tool to handle corrupted parts and yields to reasonable models, which have a higher quality than the initial segmentations.
Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.