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2013


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Camera-specific Image Denoising

Schober, M.

Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

ei pn

PDF [BibTex]

2013


PDF [BibTex]


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Statistics on Manifolds with Applications to Modeling Shape Deformations

Freifeld, O.

Brown University, August 2013 (phdthesis)

Abstract
Statistical models of non-rigid deformable shape have wide application in many fi elds, including computer vision, computer graphics, and biometry. We show that shape deformations are well represented through nonlinear manifolds that are also matrix Lie groups. These pattern-theoretic representations lead to several advantages over other alternatives, including a principled measure of shape dissimilarity and a natural way to compose deformations. Moreover, they enable building models using statistics on manifolds. Consequently, such models are superior to those based on Euclidean representations. We demonstrate this by modeling 2D and 3D human body shape. Shape deformations are only one example of manifold-valued data. More generally, in many computer-vision and machine-learning problems, nonlinear manifold representations arise naturally and provide a powerful alternative to Euclidean representations. Statistics is traditionally concerned with data in a Euclidean space, relying on the linear structure and the distances associated with such a space; this renders it inappropriate for nonlinear spaces. Statistics can, however, be generalized to nonlinear manifolds. Moreover, by respecting the underlying geometry, the statistical models result in not only more e ffective analysis but also consistent synthesis. We go beyond previous work on statistics on manifolds by showing how, even on these curved spaces, problems related to modeling a class from scarce data can be dealt with by leveraging information from related classes residing in di fferent regions of the space. We show the usefulness of our approach with 3D shape deformations. To summarize our main contributions: 1) We de fine a new 2D articulated model -- more expressive than traditional ones -- of deformable human shape that factors body-shape, pose, and camera variations. Its high realism is obtained from training data generated from a detailed 3D model. 2) We defi ne a new manifold-based representation of 3D shape deformations that yields statistical deformable-template models that are better than the current state-of-the- art. 3) We generalize a transfer learning idea from Euclidean spaces to Riemannian manifolds. This work demonstrates the value of modeling manifold-valued data and their statistics explicitly on the manifold. Specifi cally, the methods here provide new tools for shape analysis.

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pdf Project Page [BibTex]


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Modelling and Learning Approaches to Image Denoising

Burger, HC.

Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

ei

[BibTex]

[BibTex]


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Linear mixed models for genome-wide association studies

Lippert, C.

University of Tübingen, Germany, 2013 (phdthesis)

ei

[BibTex]

[BibTex]


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Modeling and Learning Complex Motor Tasks: A case study on Robot Table Tennis

Mülling, K.

Technical University Darmstadt, Germany, 2013 (phdthesis)

ei

[BibTex]

[BibTex]


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Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Models

Wang, Z.

Technical University Darmstadt, Germany, 2013 (phdthesis)

ei

[BibTex]


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Quantum kinetic theory for demagnetization after femtosecond laser pulses

Teeny, N.

Universität Stuttgart, Stuttgart, 2013 (mastersthesis)

mms

[BibTex]

[BibTex]

2007


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Some Theoretical Aspects of Human Categorization Behavior: Similarity and Generalization

Jäkel, F.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, November 2007, passed with "ausgezeichnet", summa cum laude, published online (phdthesis)

ei

PDF [BibTex]

2007


PDF [BibTex]


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Statistical Learning Theory Approaches to Clustering

Jegelka, S.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, November 2007 (diplomathesis)

ei

PDF [BibTex]

PDF [BibTex]


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Error Correcting Codes for the P300 Visual Speller

Biessmann, F.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, July 2007 (diplomathesis)

Abstract
The aim of brain-computer interface (BCI) research is to establish a communication system based on intentional modulation of brain activity. This is accomplished by classifying patterns of brain ac- tivity, volitionally induced by the user. The BCI presented in this study is based on a classical paradigm as proposed by (Farwell and Donchin, 1988), the P300 visual speller. Recording electroencephalo- grams (EEG) from the scalp while presenting letters successively to the user, the speller can infer from the brain signal which letter the user was focussing on. Since EEG recordings are noisy, usually many repetitions are needed to detect the correct letter. The focus of this study was to improve the accuracy of the visual speller applying some basic principles from information theory: Stimulus sequences of the speller have been modified into error-correcting codes. Additionally a language model was incorporated into the probabilistic letter de- coder. Classification of single EEG epochs was less accurate using error correcting codes. However, the novel code could compensate for that such that overall, letter accuracies were as high as or even higher than for classical stimulus codes. In particular at high noise levels, error-correcting decoding achieved higher letter accuracies.

ei

PDF [BibTex]

PDF [BibTex]


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Nonparametric Bayesian Discrete Latent Variable Models for Unsupervised Learning

Görür, D.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, April 2007, published online (phdthesis)

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


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Applications of Kernel Machines to Structured Data

Eichhorn, J.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, March 2007, passed with "sehr gut", published online (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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A priori Knowledge from Non-Examples

Sinz, FH.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, March 2007 (diplomathesis)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Machine Learning for Mass Production and Industrial Engineering

Pfingsten, T.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, February 2007 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Development of a Brain-Computer Interface Approach Based on Covert Attention to Tactile Stimuli

Raths, C.

University of Tübingen, Germany, University of Tübingen, Germany, January 2007 (diplomathesis)

ei

[BibTex]

[BibTex]


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A Machine Learning Approach for Estimating the Attenuation Map for a Combined PET/MR Scanner

Hofmann, M.

Biologische Kybernetik, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, 2007 (diplomathesis)

ei

[BibTex]

[BibTex]


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On the theory of magnetization dynamics of non-collinear spin systems in the s-d model

De Angeli, L.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Zur ab-initio Elektronentheorie des Magnetismus bei endlichen Temperaturen

Dietermann, F.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Röntgenzirkulardichroische Untersuchungen an ferromagnetischen verdünnten Halbleitersystemen

Tietze, T.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Low-dimensional Fe on vicinal Ir(997): Growth and magnetic properties

Kawwam, M.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Micromagnetic simulations of switching processes and the role of thermal fluctuations

Macke, S.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Physisorption von Wasserstoff in neuen Materialien mit gro\sser spezifischer Oberfläche

Schmitz, B.

Universität Bonn, Bonn, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Towards spin injection into silicon

Dash, S. P.

Universität Stuttgart, Stuttgart, 2007 (phdthesis)

mms

link (url) [BibTex]

link (url) [BibTex]


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Bestimmung der kritischen Schichtdicken ferromagnetischer Plättchen für Eindomänenverhalten

Soehnle, S.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Zeitaufgelöste Röntgenmikroskopie an magnetischen Mikrostrukturen

Puzic, A.

Universität Stuttgart, Stuttgart, 2007 (phdthesis)

mms

link (url) [BibTex]

link (url) [BibTex]


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Vortex dynamics studied by time-resolved X-ray microscopy

Chou, K. W.

Universität Stuttgart, Stuttgart, 2007 (phdthesis)

mms

link (url) [BibTex]

link (url) [BibTex]


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Resonante magnetische Reflektometrie an Ferromagnet/Paramagnet Heterostrukturen

Ferreras Paz, V.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Herstellung und Charakterisierung dünner Niob-Schichten auf verschiedenen Substraten

Mayer, M. W. R.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Formation of hard magnetic L10-FePt/FePd monolayers from elemental multilayers

Goo, N. H.

Universität Stuttgart, Stuttgart, 2007 (phdthesis)

mms

link (url) [BibTex]

link (url) [BibTex]


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Zur ab-initio Elektronentheorie stark nichtkollinearer Spinsysteme

Köberle, I.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Theorie der Kernspektroskopie mit zirkular polarisierter Gammastrahlung

Engelhart, W.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Untersuchung der Adsorption von Wasserstoff in porösen Materialien

Hönes, K.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]


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Untersuchung der mechanischen Eigenschaften dünner Chromschichten

Jüllig, P.

Universität Stuttgart, Stuttgart, 2007 (mastersthesis)

mms

[BibTex]

[BibTex]

2005


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Extension to Kernel Dependency Estimation with Applications to Robotics

BakIr, G.

Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

Abstract
Kernel Dependency Estimation(KDE) is a novel technique which was designed to learn mappings between sets without making assumptions on the type of the involved input and output data. It learns the mapping in two stages. In a first step, it tries to estimate coordinates of a feature space representation of elements of the set by solving a high dimensional multivariate regression problem in feature space. Following this, it tries to reconstruct the original representation given the estimated coordinates. This thesis introduces various algorithmic extensions to both stages in KDE. One of the contributions of this thesis is to propose a novel linear regression algorithm that explores low-dimensional subspaces during learning. Furthermore various existing strategies for reconstructing patterns from feature maps involved in KDE are discussed and novel pre-image techniques are introduced. In particular, pre-image techniques for data-types that are of discrete nature such as graphs and strings are investigated. KDE is then explored in the context of robot pose imitation where the input is a an image with a human operator and the output is the robot articulated variables. Thus, using KDE, robot pose imitation is formulated as a regression problem.

ei

PDF PDF [BibTex]

2005


PDF PDF [BibTex]


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Geometrical aspects of statistical learning theory

Hein, M.

Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Implicit Surfaces For Modelling Human Heads

Steinke, F.

Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

ei

[BibTex]

[BibTex]


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Machine Learning Methods for Brain-Computer Interdaces

Lal, TN.

Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

ei

Web [BibTex]

Web [BibTex]


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Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain

Tanner, TG.

Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005 (diplomathesis)

Abstract
A common task in psychophysics is to measure the psychometric function. A psychometric function can be described by its shape and four parameters: offset or threshold, slope or width, false alarm rate or chance level and miss or lapse rate. Depending on the parameters of interest some points on the psychometric function may be more informative than others. Adaptive methods attempt to place trials on the most informative points based on the data collected in previous trials. A new Bayesian adaptive psychometric method placing trials by minimising the expected entropy of the posterior probabilty dis- tribution over a set of possible stimuli is introduced. The method is more flexible, faster and at least as efficient as the established method (Kontsevich and Tyler, 1999). Comparably accurate (2dB) threshold and slope estimates can be obtained after about 30 and 500 trials, respectively. By using a dynamic termination criterion the efficiency can be further improved. The method can be applied to all experimental designs including yes/no designs and allows acquisition of any set of free parameters. By weighting the importance of parameters one can include nuisance parameters and adjust the relative expected errors. Use of nuisance parameters may lead to more accurate estimates than assuming a guessed fixed value. Block designs are supported and do not harm the performance if a sufficient number of trials are performed. The method was evaluated by computer simulations in which the role of parametric assumptions, its robustness, the quality of different point estimates, the effect of dynamic termination criteria and many other settings were investigated.

ei

[BibTex]

[BibTex]


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Untersuchung über die Grenzflächenmagnetisierung an (FM) Kobalt- und (AFM) Eisen-Mangan-Schichten

Harlander, M.

Stuttgart, Universität Stuttgart, 2005 (mastersthesis)

mms

[BibTex]

[BibTex]