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- Institut für Computervisualistik (46) (remove)
Today, augmented reality is becoming more and more important in several areas like industrial sectors, medicine, or tourism. This gain of importance can easily be explained by its powerful extension of real world content. Therefore, augmented realty became a way to explain and enhance the real world information. Yet, to create a system which can enhance a scene with additional information, the relation between the system and the real world must be known. In order to establish this relationship a commonly used method is optical tracking. The system calculates its relation to the real world from camera images. To do so, a reference which is known is needed in the scene to serve as an orientation. Today, this is mostly a 2D-marker or a 2D-texture. These are placed in the real world scenery to serve as a reference. But, this is an intrusion in the scene. That is why it is desirable that the system works without such an additional aid. An strategy without manipulating the scene is object-tracking. In this approach, any object from the scene can be used as a reference for the system. As an object is far more complex than a marker, it is harder for the system to establish its relationship with the real world. That is why most methods for 3D-object-tracking reduce the object by not using the whole object as reference. The focus of this thesis is to research how a whole object can be used as a reference in a way that either the system or the camera can be moved in any 360 degree angle around the object without loosing the relation to the real world. As a basis the augmented reality framework, the so called VisionLib, is used. Extensions to this system for 360 degree tracking are implemented in different ways and analyzed in the scope of this work. Also, the different extensions are compared. The best results were achieved by improving the reinitialization process. With this extension, current camera images of the scene are given to the system. With the hek of these images, the system can calculate the relation to the real world faster in case the relation went missing.
With the emergence of current generation head-mounted displays (HMDs), virtual reality (VR) is regaining much interest in the field of medical imaging and diagnosis. Room-scale exploration of CT or MRI data in virtual reality feels like an intuitive application. However in VR retaining a high frame rate is more critical than for conventional user interaction seated in front of a screen. There is strong scientific evidence suggesting that low frame rates and high latency have a strong influence on the appearance of cybersickness. This thesis explores two practical approaches to overcome the high computational cost of volume rendering for virtual reality. One lies within the exploitation of coherency properties of the especially costly stereoscopic rendering setup. The main contribution is the development and evaluation of a novel acceleration technique for stereoscopic GPU ray casting. Additionally, an asynchronous rendering approach is pursued to minimize the amount of latency in the system. A selection of image warping techniques has been implemented and evaluated methodically, assessing the applicability for VR volume rendering.
Since the invention of U-net architecture in 2015, convolutional networks based on its encoder-decoder approach significantly improved results in image analysis challenges. It has been proven that such architectures can also be successfully applied in different domains by winning numerous championships in recent years. Also, the transfer learning technique created an opportunity to push state-of-the-art benchmarks to a higher level. Using this approach is beneficial for the medical domain, as collecting datasets is generally a difficult and expensive process.
In this thesis, we address the task of semantic segmentation with Deep Learning and make three main contributions and release experimental results that have practical value for medical imaging.
First, we evaluate the performance of four neural network architectures on the dataset of the cervical spine MRI scans. Second, we use transfer learning from models trained on the Imagenet dataset and compare it to randomly initialized networks. Third, we evaluate models trained on the bias field corrected and raw MRI data. All code to reproduce results is publicly available online.
Simulation of fractures
(2014)
Real-time computing often avoids the simulation of fractures due to its complexity. The field of engineering science provides methods to create these simulations to improve games and other applications. Steadily rising computer capacities allow suitable simulations on a real-time basis and make this aspect increasingly interesting. The topic and aim of this research is to simulate fractures of stiff bodies. The primary objective is the physical plausibility and performance of the application. This thesis analyses the potential of computer science to realize the simulation of fractures.
Three existing as well as one self-created were implemented and analysed. The works "Real time simulation of deformation and Fracture of stiff material" from Müller et al., "real time simulation of Brittle Fracture using Modal analysis" from Glondu et al. and "Fast and Controllable simulation of the Shattering of Brittle Objects" from Smith et al. form the basis of this thesis. The introduced methods use different computation of forces and fractures. The developed procedure uses the idea of generating secondary breaks. The approaches were implemented based on the Bullet physics-engine. The results of the work show that physically based breaks are realizable on a real-time basis.
The analysis of the physical methods demonstrates that their performance mainly depends on the constitution of the used objects. This thesis shows that the further investigation of this topic can discover new possibilities. The improvement of the realism in virtual worlds can be achieved by executing physically plausible methods.
In recent years head mounted displays (HMD) and their abilities to create virtual realities comparable with the real world moved more into the focus of press coverage and consumers. The reason for this lies in constant improvements in available computing power, miniaturisation of components as well as the constantly shrinking power consumption. These trends originate in the general technical progress driven by advancements made in smartphone sector. This gives more people than ever access to the required components to create these virtual realities. However at the same time there is only limited research which uses the current generation of HMDs especially when comparing the virtual and real world against each other. The approach of this thesis is to look into the process of navigating both real and virtual spaces while using modern hardware and software. One of the key areas are the spatial and peripheral perception without which it would be difficult to navigate a given space. The influence of prior real and virtual experiences on these will be another key aspect. The final area of focus is the influence on the emotional state and how it compares to the real world. To research these influences a experiment using the Oculus Rift DK2 HMD will be held in which subjects will be guided through a real space as well as a virtual model of it. Data will be gather in a quantitative manner by using surveys. Finally, the findings will be discussed based on a statistical evaluation. During these tests the different perception of distances and room size will the compared and how they change based on the current reality. Furthermore, the influence of prior spatial activities both in the real and the virtual world will looked into. Lastly, it will be checked how real these virtual worlds are and if they are sufficiently sophisticated to trigger the same emotional responses as the real world.
Constituent parsing attempts to extract syntactic structure from a sentence. These parsing systems are helpful in many NLP applications such as grammar checking, question answering, and information extraction. This thesis work is about implementing a constituent parser for German language using neural networks. Over the past, recurrent neural networks have been used in building a parser and also many NLP applications. In this, self-attention neural network modules are used intensively to understand sentences effectively. With multilayered self-attention networks, constituent parsing achieves 93.68% F1 score. This is improved even further by using both character and word embeddings as a representation of the input. An F1 score of 94.10% was the best achieved by constituent parser using only the dataset provided. With the help of external datasets such as German Wikipedia, pre-trained ELMo models are used along with self-attention networks achieving 95.87% F1 score.
Einfluss eines Ausrichtungswerkzeugs auf die Bedienbarkeit in unbeaufsichtigten Eyetrackingsystemen
(2015)
Eye gaze trackers are devices that can estimate the direction of gaze of a person. Among usability testing eye tracking also allows persons with decreased limb mobility to control or to interact with the computer. The quality and availability of eye tracking equipment has been increasing while costs have been decreasing. This development leads to entering new markets by using eye tracking as an additional input dimension for a variety of applications. Up to now eye tracking has been supervised by qualified experts, who assured that the important conditions like position in front of the eye tracking device, calibration and light conditions has been kept, while using.
This thesis examines an adjustment tool, which is helping the user to adjust in front of the eye tracker and helping to keep this position during the experiment. Furthermore the accuracy while moving the head has been analysed. In this experiment an remote eye gaze tracker has been used to control a game character in the video game called 'Schau Genau!'. The goal was to determine whether the game is playable without the barrier of adjusting and calibration. The results show that adjusting in front of an eye tracker is not a problem, keeping this position is. Small changes of the head position after the calibration process leads to a lack of accuracy. Giving up the calibration and using someone else calibration shows way bigger deviation. Additional head movement increases error rate and makes controlling more difficult.
This thesis presents a prototypical application for speech therapy as a therapeutical tool, simulating the articulation of German phonemes and the swallowing reflex. A special attention is given to a three-dimensional visualization of anatomical models of the pharyngolaryngeal region, which can be used in an interactive way. For examining the benefits of such an application in relation to conventional therapy mediums, the thesis considers iteratively the requirements of speech therapists.
In current research of the autonomous mobile robots, path planning is still a very important issue.
This master's thesis deals with various path planning algorithms for the navigation of such mobile systems. This is not only to determine a collision-free trajectory from one point to another. The path should still be optimal and comply with all vehicle-given constraints. Especially the autonomous driving in an unknown and dynamic environment poses a major challenge, because a closed-loop control is necessary and thus a certain dynamic of the planner is demanded.
In this paper, two types of algorithms are presented. First, the path planner, based on A*, which is a common graph search algorithm: A*, Anytime Repairing A*, Lifelong Planning A*, D* Lite, Field D*, hybrid A*. Second, the algorithms which are based on the probabilistic planning algorithm Rapidly-exploring Random Tree (Rapidly-exploring Random Tree, RRT*, Lifelong Planning RRT*), as well as some extensions and heuristics. In addition, methods for collision avoidance and path smoothing are presented. Finally, these different algorithms are evaluated and compared with each other.
Unterschiedliche Quellen (Print-Medien, Fernsehberichte u. Ä.) berichten immer wieder davon, dass es mit der Datenschutzkompetenz bei Kindern und Jugendlichen schlecht bestellt ist. Daher ist dem Thema Datenschutz im Informatikunterricht eine besondere Bedeutung zuzuschreiben.
Im Rahmen der Dissertation von Herrn Hug wird ein Datenschutzkompetenzmodell [Quelle INFOS17] entwickelt, anhand dessen die Datenschutzkompetenz von Schülerinnen und Schülern im Altern von 10 bis 13 Jahren gemessen werden kann.
Im Rahmen dieser Masterarbeit werden existierende Unterrichtsmaterialien zum Thema Datenschutz gesammelt und dazu eine Unterrichtsreihe entwickelt. Hierbei werden auch eigene Zugänge aufzeigt, um ein kohärentes und abgeschlossenes Projekt zu entwerfen, bei dem aktuelle Gefahren für Schülerinnen und Schüler aufgezeigt werden. Ziel ist es, dass die Schülerinnen und Schüler dazu befähigt werden, ihr Verhalten bezüglich Datenschutz besser einzuschätzen und verantwortungsvoller mit ihren persönlichen Daten umzugehen. Im Rahmen eines Feldversuches in einer 6. Klasse eines Gymnasiums wurde die Unterrichtsreihe erprobt.