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Human action recognition from a video has received growing attention in computer vision and has made significant progress in recent years. Action recognition is described as a requirement to decide which human actions appear in videos. The difficulties involved in distinguishing human actions are due to the high complexity of human behaviors as well as appearance variation, motion pattern variation, occlusions, etc. Many applications use human action recognition on captured video from cameras, resulting in video surveillance systems, health monitoring, human-computer interaction, and robotics. Action recognition based on RGB-D data has increasingly drawn more attention to it in recent years. RGB-D data contain color (Red, Green, and Blue (RGB)) and depth data that represent the distance from the sensor to every pixel in the object (object point). The main problem that this thesis deals with is how to automate the classification of specific human activities/actions through RGB-D data. The classification process of these activities utilizes a spatial and temporal structure of actions. Therefore, the goal of this work is to develop algorithms that can distinguish these activities by recognizing low-level and high-level activities of interest from one another. These algorithms are developed by introducing new features and methods using RGB-D data to enhance the detection and recognition of human activities. In this thesis, the most popular state-of-the-art techniques are reviewed, presented, and evaluated. From the literature review, these techniques are categorized into hand-crafted features and deep learning-based approaches. The proposed new action recognition framework is based on these two categories that are approved in this work by embedding novel methods for human action recognition. These methods are based on features extracted from RGB-D data that are
evaluated using machine learning techniques. The presented work of this thesis improves human action recognition in two distinct parts. The first part focuses on improving current successful hand-crafted approaches. It contributes into two significant areas of state-of-the-art: Execute the existing feature detectors, and classify the human action in the 3D spatio-temporal domains by testing a new combination of different feature representations. The contributions of this part are tested based on machine learning techniques that include unsupervised and supervised learning to evaluate this suitability for the task of human action recognition. A k-means clustering represents the unsupervised learning technique, while the supervised learning technique is represented by: Support Vector Machine, Random Forest, K-Nearest Neighbor, Naive Bayes, and Artificial Neural Networks classifiers. The second part focuses on studying the current deep-learning-based approach and how to use it with RGB-D data for the human action recognition task. As the first step of each contribution, an input video is analyzed as a sequence of frames. Then, pre-processing steps are applied to the video frames, like filtering and smoothing methods to remove the noisy data from each frame. Afterward, different motion detection and feature representation methods are used to extract features presented in each frame. The extracted features
are represented by local features, global features, and feature combination besides deep learning methods, e.g., Convolutional Neural Networks. The feature combination achieves an excellent accuracy performance that outperforms other methods on the same RGB-D datasets. All the results from the proposed methods in this thesis are evaluated based on publicly available datasets, which illustrate that using spatiotemporal features can improve the recognition accuracy. The competitive experimental results are achieved overall. In particular, the proposed methods can be better applied to the test set compared to the state-of-the-art methods using the RGB-D datasets.
Point Rendering
(2021)
In this thesis different methods for rendering point data are shown and compared with each other. The methods can be divided into two categories. For one visual methods are introduced that strictly deal with the displaying of point primitves. The main problem here lies in the depiction of surfaces since point data, unlike traditional triangle meshes, doesn't contain any connectivity information. On the other hand data strucutres are shown that enable real-time rendering of large point clouds. Point clouds often contain large amounts of data since they are mostly generated through 3D scanning processes such as laser scanning and photogrammetry.
Das Hauptziel der vorliegenden Arbeit ist die Absicherung der Qualität eines pharmazeutischen Produktionsprozesses durch die Überprüfung des Volumens mikroskopischer Polymerstäbchen mit einem hochgenauen 3D Messverfahren. Die Polymerstäbchen werden für pharmazeutische Anwendungen hergestellt. Aus Gründen der Qualitätssicherung muss das Istgewicht überprüft werden. Derzeit werden die Polymerstäbchen stichprobenartig mit einer hochpräzisen Waage gewogen. Für die nächste Generation von Polymeren wird angenommen, dass die Produktabmessungen weiter reduziert werden sollen und die Produktionstoleranzen auf 2,5% gesenkt werden. Die daraus resultierenden Genauigkeitsanforderungen übersteigen jedoch die Möglichkeiten der Wiegetechnik. Bei homogenen Materialien ist die Masse proportional zum Volumen. Aus diesem Grund kommt dessen Bestimmung als Alternative in Frage. Dies verschafft Zugang zu optischen Messverfahren und deren Flexibilität und Genauigkeitpotenzial. Für den Entwurf eines auf die Fragestellung angepassten Messkonzeptes sind weiterhin von Bedeutung, dass das Objekt kontaktlos, mit einer Taktzeit von maximal fünf Sekunden vermessen und das Volumen approximiert wird. Die Querschnitte der Polymerstäbchen sind etwa kreisförmig. Aufgrund der Herstellung der Fragmente kann nicht davon ausgegangen werden, dass die Anlageflächen orthogonal zur Symmetrieachse des Objektes sind. Daher muss analysiert werden, wie sich kleine Abweichungen von kreisförmigen Querschnitten sowie die nicht idealen Anlageflächen auswirken. Die maximale Standardabweichung für das Volumen, die nicht überschritten werden sollte, beträgt 2,5%. Dies entspricht einer maximalen Abweichung der Querschnittsfläche um 1106 µm² (Fehlerfortpfanzung). Als Bewertungskriterium wird der Korrelationskoeffzient zwischen den gemessenen Volumina und den Massen bestimmt. Ein ideales Ergebnis wäre 100%. Die Messung zielt auf einen Koeffzienten von 98% ab. Um dies zu erreichen, ist ein präzises Messverfahren für Volumen erforderlich. Basierend auf dem aktuellen Stand der Technik können die vorhandenen optischen Messverfahren nicht verwendet werden. Das Polymerstäbchen wird von einer Kamera im Durchlicht beobachtet. Daher sind der Durchmesser und die Länge sichtbar. Das Objekt wird mittels einer mechanischen Vorrichtung um die Längsachse gedreht. So können Bilder von allen Seiten aufgenommen werden. Der Durchmesser und die Länge werden mit der Bildverarbeitung berechnet. Das neue Konzept vereint die Vorteile der Verfahren: Es ist unempfindlich gegen Farb-/Helligkeitsänderungen und die Bilder können in beliebiger Anzahl aufgenommen werden. Außerdem sind die Erfassung und Auswertung wesentlich schneller. Es wird ein Entwurf und die Umsetzung einer Lösung zur hochpräzisen Volumenmessung von Polymerstäbchen mit optischer Messtechnik und Bildverarbeitung ausgearbeitet. Diese spezielle Prozesslösung in der Prozesslinie (inline) sollte eine 100%ige Qualitätskontrolle während der Produktion garantieren. Die Zykluszeiten des Systems sollte fünf Sekunden pro Polymerstäbchen nicht überschreiten. Die Rahmenbedienungen für den Prozess sind durch die Materialeigenschaften des Objekts, die geringe Objektgröße (Breite = 199 µm, Länge = 935 µm bis 1683 µm) und die undeffinierte Querschnittsform (durch den Trocknungsprozess) vorgegeben. Darüber hinaus sollten die Kosten für den Prozess nicht zu hoch sein. Der Messaufbau sollte klein sein und ohne Sicherheitsvorkehrungen oder Abschirmungen arbeiten. Das entstandene System nimmt die Objekte in verschiedenen Winkelschritten auf, wertet mit Hilfe der Bildverarbeitung die Aufnahmen aus und approximiert das Volumen. Der Korrelationskoffizient zwischen Volumen und Gewicht beträgt für 77 Polymerstäbchen mit einem Gewicht von 37 µg bis 80 µg 99; 87%. Mit Hilfe eines Referenzsystems kann die Genauigkeit der Messung bestimmt werden. Die Standardabweichung sollte maximal 2,5% betragen. Das entstandene System erzielt eine maximale Volumenabweichung von 1,7%. Die Volumenvermessung erfüllt alle Anforderungen und kann somit als Alternative für die Waage verwendet werden.
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.
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.
In der Computergrafik stellte die Berechnung von Reflexionen lange ein
Problem dar. Doch mit der ständigen Weiterentwicklung der Hardware
und Vorstellung neuer Verfahren ist eine realitätsnahe,
echtzeitfähige(durchschnittlich 60 FPS) Berechnung von Reflexionen möglich. In der folgenden Ausarbeitung werden verschiedene Reflexionsverfahren vorgestellt. Alle mathematischen und physikalischen Grundlagen werden gegeben, um die Algorithmen nachvollziehen zu können. Da eine Reflexion immer das Abtasten eines reflektierten Vektors bedeutet, werden zwei verschiedene Abtastungsverfahren für blickabhängige Reflexionen vorgestellt und anschließend implementiert. Zuletzt werden die Verfahren auf Basis von Qualität und Performance gegenübergestellt.
In dieser Arbeit wird die Konzeption, Implementierung und Evaluierung einer Augmented Reality-App beschrieben. Diese wurde mit dem Ziel entwickelt, Objekte im realen Raum mit virtuellen Hilfsmitteln auszumessen, sodass diese Anwendung einen Holzgliedermaßstab ersetzen kann. Hinzu kommt die praktische Speicherung der Messwerte. Angefertigt wurde die App mit der Unity Engine und programmiert in C#.
Schwerpunkte dieser Arbeit sind die Benutzerfreundlichkeit der App, sowie die Eignung von AR Foundation für das Ausmessungstool.
Die Anwendung wird auf die genannten Kriterien im Rahmen eines Nutzertests in einer abschließenden Evaluation bewertet.
Als Ergebnis ließ sich festhalten, dass sich die AR-App noch im Prototyp-Stadium befindet, aber im Allgemeinen schon als benutzerfreundlich gilt. Kleinere Änderungen sollen und müssen noch vorgenommen werden, um auch den Umgang mit dem AR-Tool zu vereinfachen.
Studies in recent years have demonstrate adolescents and young adults to have a deficient data protection competence, however children and adolescents between the ages of ten and 13 were mostly not focus of these studies. Therefore, the guiding question of the work is how data protection competence is developed in children and adolescents at a young age in order to be able to infer suitable, educational concepts for this age group. At the beginning of the work, a data protection competence model is derived from a media competence model, which serves as the basis for the further field investigation. A survey was carried out at general secondary schools in Rhineland-Palatinate, which shows that the respondents still have sufficiently developed Risk Assessment Competence, but were insufficiently developed in terms of knowledge, Selection and Usage Competence and the Implementation Competence. Recommendations for actions are given in the last part of the work – containing learning goal descriptions to be possibly implemented in an educational framework – in order to address this issue.
The Material Point Method (MPM) has proven to be a very capable simulation method in computer graphics that is able to model materials that were previously very challenging to animate [1, 2]. Apart from simulating singular materials, the simulation of multiple materials that interact with each other introduces new challenges. This is the focus of this thesis. It will be shown that the self-collision capabilities of the MPM can naturally handle multiple materials interacting in the same scene on a collision basis, even if the materials use distinct constitutive models. This is then extended by porous interaction of materials as in[3], which also integrates easily with MPM.It will furthermore be shown that regular single-grid MPM can be viewed as a subset of this multi-grid approach, meaning that its behavior can also be achieved if multiple grids are used. The porous interaction is generalized to arbitrary materials and freely changeable material interaction terms, yielding a flexible, user-controllable framework that is independent of specific constitutive models. The framework is implemented on the GPU in a straightforward and simple way and takes advantage of the rasterization pipeline to resolve write-conflicts, resulting in a portable implementation with wide hardware support, unlike other approaches such as [4].
In the context of augmented reality we define tracking as a collection of methods to obtain the position and orientation (pose) of a user. By means of various displaying techniques, this ensures a correct visual overlay of graphical information onto the reality perceived. Precise results for calculation of the camera pose are gained by methods of image processing, usually analyzing the pixels of an image and extracing features, which can be recognized over the image sequence. However, these methods do not regard the process of image synthesis or at least in a very simplyfied way. In contrast, the class of model-based methods assumes a given 3D model of the observed scene. Based on the model data features can be identified to establish correspondences in the camera image. From these feature correspondences the camera pose is calculated. An interesting approach is the strategy of analysis-by-synthesis, regarding the computer graphics rendering process for extending the knowledge about the model by information from image synthesis and other environment variables.
In this thesis the components of a tracking system are identified and further it is analyzed, to what extend information about the model, the rendering process and the environment can contribute to the components for improvement of the tracking process using analysis-by-synthesis. In particular, by using knowledge as topological information, lighting or perspective, the feature synthesis and correspondence finding should lead to visually unambiguous features that can be predicted and evaluated to be suitable for stable tracking of the camera pose.
Bio-medical data comes in various shapes and with different representations.
Domain experts use such data for analysis or diagnosis,
during research or clinical applications. As the opportunities to obtain
or to simulate bio-medical data become more complex and productive,
the experts face the problem of data overflow. Providing a
reduced, uncluttered representation of data, that maintains the data’s
features of interest falls into the area of Data Abstraction. Via abstraction,
undesired features are filtered out to give space - concerning the
cognitive and visual load of the viewer - to more interesting features,
which are therefore accentuated. To address this challenge, the dissertation
at hand will investigate methods that deal with Data Abstraction
in the fields of liver vasculature, molecular and cardiac visualization.
Advanced visualization techniques will be applied for this purpose.
This usually requires some pre-processing of the data, which will also
be covered by this work. Data Abstraction itself can be implemented
in various ways. The morphology of a surface may be maintained,
while abstracting its visual cues. Alternatively, the morphology may
be changed to a more comprehensive and tangible representation.
Further, spatial or temporal dimensions of a complex data set may
be projected to a lower space in order to facilitate processing of the
data. This thesis will tackle these challenges and therefore provide an
overview of Data Abstraction in the bio-medical field, and associated
challenges, opportunities and solutions.
Molecular dynamics (MD) as a field of molecular modelling has great potential to revolutionize our knowledge and understanding of complex macromolecular structures. Its field of application is huge, reaching from computational chemistry and biology over material sciences to computer-aided drug design. This thesis on one hand provides insights into the underlying physical concepts of molecular dynamics simulations and how they are applied in the MD algorithm, and also briefly illustrates different approaches, as for instance the molecular mechanics and molecular quantum mechanics approaches.
On the other hand an own all-atom MD algorithm is implemented utilizing and simplifying a version of the molecular mechanics based AMBER force field published by \big[\cite{cornell1995second}\big]. This simulation algorithm is then used to show by the example of oxytocin how individual energy terms of a force field function. As a result it has been observed, that applying the bond stretch forces alone caused the molecule to be compacted first in certain regions and then as a whole, and that with adding more energy terms the molecule got to move with increasing flexibility.
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.
In dieser Arbeit wird das Echtzeitrendering von Wolken von der Theorie bis hin zur Entwicklung derselben behandelt. Dabei sollen die visuellen Eigenschaften der Wolken sowie die unterschiedliche Wolkentypen simuliert werden. Dabei ist die Berechnung der Beleuchtung essentiell für ein glaubwürdiges Ergebnis. Die Rendertechniken nutzen dabei unterschiedliche Noise-Texturen; für die Modulierung der Wolken sind es hauptsächlich Perlin- und Perlin-Worley-Texturen. Das Rendern der Wolken wird per Compute-Shader durchgeführt um die Echtzeitfähigkeit zu gewährleisten. Um die Performance zu steigern, werden Temporal Reprojektion und andere Optimierungstechniken angewendet.
This thesis is about the design and the implementation of a virtual reality experience. The goal is to answer two questions: Is it possible to create an immersive virtual reality experience which is mainly using impulses and triggers to scare and frighten users? Secondly, is this immersion strong enough to create an illusion in which the user can't separate the real world from the virtual world? To realise this project the design program Unity3D as well as Visual Studios 2017 were used. Furthermore, in order to verify that the experience is indeed immersive for the user, an experiment with a sample size of seven people was created. Afterwards the candidates were interviewed via a questionnaire how they felt during the virtual reality application. As a result the study showed that the application has tendencies to be immersive but the users were still aware of the situation. It can be concluded that the immersion was not strong enough to fool users regarding the separation of virtual and real world.
In order to plan the interior of a room, various programs for computers,
smart phones or head-mounted displays are available. The transfer to the
real environment is a difficult task. Therefore an augmented reality approach
is developed to illustrate the planning in the real room. If several
people want to contribute their ideas, conventional systems require to
work on one device together. The aim of this master thesis is to design and
develop a collaborative spatial planning application in augmented reality.
The application is developed in Unity with ARCore and C#.
This bachelor thesis implements a system for camera tracking based on a particle filter. For this purpose, a marker tracking is realized and the camera position is calculated based on the marker position. The marker is to be found with a particle filter and in order to accomplish this possible marker positions are simulated, also called particles, and weighted with Likelyhood-Functions. The focus lies on the evaluation of different Likelihood-Functions of the particle filter. The Likelyhood functions were implemented in CUDA as part of the implementation.
Clubs, such as Scouts, rely on the work of their volunteer members, who have a variety of tasks to accomplish. Often there are sudden changes in their organization teams and offices, whereby planning steps are lost and inexperience in planning occurs. Since the special requirements are not covered by already existing tools, ScOuT, a planning tool for the organization administration, is designed and developed in this work to support clubs with regard to the mentioned problems. The focus was on identifying and using various suitable guidelines and heuristic methods to create a usable interface. The developed product was evaluated empirically by a user survey in terms of usability.
The result of this study shows that already a high degree of the desired goal could be reached by the inclusion of the guidelines and methods. From this it can be concluded that with the help of user-specific concept ideas and the application of suitable guidelines and methods, a suitable basis for a usable application to support clubs can be created.
This thesis deals with the conception and implementation of an action role-playing game using the game engine Unity. Within the context of an evaluation, the game was supposed to be evaluated with regard to the usability of the integrated control modes, the visual conviction of the animations and the user-friendliness of the tools and visualizations provided. In addition, weaknesses and problems in the game were to be identified through open feedback. The results of the evaluation showed that the game is still expandable in terms of usability and user-friendliness, but has left a good impression on the test persons.