Header logo is


2020


Thumb xl aaai
Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

Rueegg, N., Lassner, C., Black, M. J., Schindler, K.

In Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), Febuary 2020 (inproceedings)

Abstract
The goal of many computer vision systems is to transform image pixels into 3D representations. Recent popular models use neural networks to regress directly from pixels to 3D object parameters. Such an approach works well when supervision is available, but in problems like human pose and shape estimation, it is difficult to obtain natural images with 3D ground truth. To go one step further, we propose a new architecture that facilitates unsupervised, or lightly supervised, learning. The idea is to break the problem into a series of transformations between increasingly abstract representations. Each step involves a cycle designed to be learnable without annotated training data, and the chain of cycles delivers the final solution. Specifically, we use 2D body part segments as an intermediate representation that contains enough information to be lifted to 3D, and at the same time is simple enough to be learned in an unsupervised way. We demonstrate the method by learning 3D human pose and shape from un-paired and un-annotated images. We also explore varying amounts of paired data and show that cycling greatly alleviates the need for paired data. While we present results for modeling humans, our formulation is general and can be applied to other vision problems.

ps

pdf [BibTex]

2020


pdf [BibTex]

2002


no image
Surface-slant-from-texture discrimination: Effects of slant level and texture type

Rosas, P., Wichmann, F., Wagemans, J.

Journal of Vision, 2(7):300, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)

Abstract
The problem of surface-slant-from-texture was studied psychophysically by measuring the performances of five human subjects in a slant-discrimination task with a number of different types of textures: uniform lattices, randomly displaced lattices, polka dots, Voronoi tessellations, orthogonal sinusoidal plaid patterns, fractal or 1/f noise, “coherent” noise and a “diffusion-based” texture (leopard skin-like). The results show: (1) Improving performance with larger slants for all textures. (2) A “non-symmetrical” performance around a particular slant characterized by a psychometric function that is steeper in the direction of the more slanted orientation. (3) For sufficiently large slants (66 deg) there are no major differences in performance between any of the different textures. (4) For slants at 26, 37 and 53 degrees, however, there are marked differences between the different textures. (5) The observed differences in performance across textures for slants up to 53 degrees are systematic within subjects, and nearly so across them. This allows a rank-order of textures to be formed according to their “helpfulness” — that is, how easy the discrimination task is when a particular texture is mapped on the surface. Polka dots tended to allow the best slant discrimination performance, noise patterns the worst up to the large slant of 66 degrees at which performance was almost independent of the particular texture chosen. Finally, our large number of 2AFC trials (approximately 2800 trials per texture across subjects) and associated tight confidence intervals may enable us to find out about which statistical properties of the textures could be responsible for surface-slant-from-texture estimation, with the ultimate goal of being able to predict observer performance for any arbitrary texture.

ei

Web DOI [BibTex]

2002


Web DOI [BibTex]


no image
Modelling Contrast Transfer in Spatial Vision

Wichmann, F.

Journal of Vision, 2(10):7, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)

Abstract
Much of our information about spatial vision comes from detection experiments involving low-contrast stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast, the results of which allow different models of contrast processing (e.g. energy versus gain-control models) to be critically assessed (Wichmann & Henning, 1999). Studies of detection and discrimination using pulse train stimuli in noise, on the other hand, make predictions about the number, position and properties of noise sources within the processing stream (Henning, Bird & Wichmann, 2002). Here I report modelling results combining data from both sinusoidal and pulse train experiments in and without noise to arrive at a more tightly constrained model of early spatial vision.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Gender Classification of Human Faces

Graf, A., Wichmann, F.

In Biologically Motivated Computer Vision, pages: 1-18, (Editors: Bülthoff, H. H., S.W. Lee, T. A. Poggio and C. Wallraven), Springer, Berlin, Germany, Second International Workshop on Biologically Motivated Computer Vision (BMCV), November 2002 (inproceedings)

Abstract
This paper addresses the issue of combining pre-processing methods—dimensionality reduction using Principal Component Analysis (PCA) and Locally Linear Embedding (LLE)—with Support Vector Machine (SVM) classification for a behaviorally important task in humans: gender classification. A processed version of the MPI head database is used as stimulus set. First, summary statistics of the head database are studied. Subsequently the optimal parameters for LLE and the SVM are sought heuristically. These values are then used to compare the original face database with its processed counterpart and to assess the behavior of a SVM with respect to changes in illumination and perspective of the face images. Overall, PCA was superior in classification performance and allowed linear separability.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


no image
Insect-Inspired Estimation of Self-Motion

Franz, MO., Chahl, JS.

In Biologically Motivated Computer Vision, (2525):171-180, LNCS, (Editors: Bülthoff, H.H. , S.W. Lee, T.A. Poggio, C. Wallraven), Springer, Berlin, Germany, Second International Workshop on Biologically Motivated Computer Vision (BMCV), November 2002 (inproceedings)

Abstract
The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. In this study, we examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge about the environment. The optimal estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates turn out to be less reliable.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


no image
Pulse train detection and discrimination in pink noise

Henning, G., Wichmann, F., Bird, C.

Journal of Vision, 2(7):229, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)

Abstract
Much of our information about spatial vision comes from detection experiments involving low-contrast stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast. We explored both detection and contrast discrimination performance with sinusoidal and "pulse-train" (or line) gratings. Both types of grating had a fundamental spatial frequency of 2.09-c/deg but the pulse-train, ideally, contains, in addition to its fundamental component, all the harmonics of the fundamental. Although the 2.09-c/deg pulse-train produced on the display was measured and shown to contain at least 8 harmonics at equal contrast, it was no more detectable than its most detectable component; no benefit from having additional information at the harmonics was measurable. The addition of broadband "pink" noise, designed to equalize the detectability of the components of the pulse train, made it about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with an in-phase pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not improve the discrimination performance of the pulse train relative to that of its sinusoidal components. In contrast, a 2.09-c/deg "super train," constructed to have 8 equally detectable harmonics, was a factor of five more detectable than any of its components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Combining sensory Information to Improve Visualization

Ernst, M., Banks, M., Wichmann, F., Maloney, L., Bülthoff, H.

In Proceedings of the Conference on Visualization ‘02 (VIS ‘02), pages: 571-574, (Editors: Moorhead, R. , M. Joy), IEEE, Piscataway, NJ, USA, IEEE Conference on Visualization (VIS '02), October 2002 (inproceedings)

Abstract
Seemingly effortlessly the human brain reconstructs the three-dimensional environment surrounding us from the light pattern striking the eyes. This seems to be true across almost all viewing and lighting conditions. One important factor for this apparent easiness is the redundancy of information provided by the sensory organs. For example, perspective distortions, shading, motion parallax, or the disparity between the two eyes' images are all, at least partly, redundant signals which provide us with information about the three-dimensional layout of the visual scene. Our brain uses all these different sensory signals and combines the available information into a coherent percept. In displays visualizing data, however, the information is often highly reduced and abstracted, which may lead to an altered perception and therefore a misinterpretation of the visualized data. In this panel we will discuss mechanisms involved in the combination of sensory information and their implications for simulations using computer displays, as well as problems resulting from current display technology such as cathode-ray tubes.

ei

PDF Web [BibTex]

PDF Web [BibTex]


no image
Incorporating Invariances in Non-Linear Support Vector Machines

Chapelle, O., Schölkopf, B.

In Advances in Neural Information Processing Systems 14, pages: 609-616, (Editors: TG Dietterich and S Becker and Z Ghahramani), MIT Press, Cambridge, MA, USA, 15th Annual Neural Information Processing Systems Conference (NIPS), September 2002 (inproceedings)

Abstract
The choice of an SVM kernel corresponds to the choice of a representation of the data in a feature space and, to improve performance, it should therefore incorporate prior knowledge such as known transformation invariances. We propose a technique which extends earlier work and aims at incorporating invariances in nonlinear kernels. We show on a digit recognition task that the proposed approach is superior to the Virtual Support Vector method, which previously had been the method of choice.

ei

PDF Web [BibTex]

PDF Web [BibTex]


no image
Kernel Dependency Estimation

Weston, J., Chapelle, O., Elisseeff, A., Schölkopf, B., Vapnik, V.

(98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)

Abstract
We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images.

ei

PDF [BibTex]

PDF [BibTex]


no image
Phase information in the recognition of natural images

Braun, D., Wichmann, F., Gegenfurtner, K.

Perception, 31(ECVP Abstract Supplement):133, 25th European Conference on Visual Perception, August 2002 (poster)

Abstract
Fourier phase plays an important role in determining global image structure. For example, when the phase spectrum of an image of a flower is swapped with that of a tank, we usually perceive a tank, even though the amplitude spectrum is still that of the flower. Similarly, when the phase spectrum of an image is randomly swapped across frequencies, that is its Fourier energy is randomly distributed over the image, the resulting image becomes impossible to recognise. Our goal was to evaluate the effect of phase manipulations in a quantitative manner. Subjects viewed two images of natural scenes, one of which contained an animal (the target) embedded in the background. The spectra of the images were manipulated by adding random phase noise at each frequency. The phase noise was the independent variable, uniformly distributed between 0° and ±180°. Subjects were remarkably resistant to phase noise. Even with ±120° noise, subjects were still 75% correct. The proportion of correct answers closely followed the correlation between original and noise-distorted images. Thus it appears as if it was not the global phase information per se that determines our percept of natural images, but rather the effect of phase on local image features.

ei

Web [BibTex]

Web [BibTex]


no image
Detection and discrimination in pink noise

Wichmann, F., Henning, G.

5, pages: 100, 5. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2002 (poster)

Abstract
Much of our information about early spatial vision comes from detection experiments involving low-contrast stimuli, which are not, perhaps, particularly "natural" stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast whilst keeping the number of unknown parameters comparatively small. We explored both detection and contrast discrimination performance with sinusoidal and "pulse-train" (or line) gratings. Both types of grating had a fundamental spatial frequency of 2.09-c/deg but the pulse-train, ideally, contains, in addition to its fundamental component, all the harmonics of the fundamental. Although the 2.09-c/deg pulse-train produced on our display was measured using a high-performance digital camera (Photometrics) and shown to contain at least 8 harmonics at equal contrast, it was no more detectable than its most detectable component; no benefit from having additional information at the harmonics was measurable. The addition of broadband 1-D "pink" noise made it about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with an in-phase pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not improve the discrimination performance of the pulse train relative to that of its sinusoidal components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.

ei

Web [BibTex]

Web [BibTex]


no image
A compression approach to support vector model selection

von Luxburg, U., Bousquet, O., Schölkopf, B.

(101), Max Planck Institute for Biological Cybernetics, 2002, see more detailed JMLR version (techreport)

Abstract
In this paper we investigate connections between statistical learning theory and data compression on the basis of support vector machine (SVM) model selection. Inspired by several generalization bounds we construct ``compression coefficients'' for SVMs, which measure the amount by which the training labels can be compressed by some classification hypothesis. The main idea is to relate the coding precision of this hypothesis to the width of the margin of the SVM. The compression coefficients connect well known quantities such as the radius-margin ratio R^2/rho^2, the eigenvalues of the kernel matrix and the number of support vectors. To test whether they are useful in practice we ran model selection experiments on several real world datasets. As a result we found that compression coefficients can fairly accurately predict the parameters for which the test error is minimized.

ei

[BibTex]

[BibTex]


no image
Application of Monte Carlo Methods to Psychometric Function Fitting

Wichmann, F.

Proceedings of the 33rd European Conference on Mathematical Psychology, pages: 44, 2002 (poster)

Abstract
The psychometric function relates an observer's performance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. Here I describe methods to (1) fitting psychometric functions, (2) assessing goodness-of-fit, and (3) providing confidence intervals for the function's parameters and other estimates derived from them. First I describe a constrained maximum-likelihood method for parameter estimation. Using Monte-Carlo simulations I demonstrate that it is important to have a fitting method that takes stimulus-independent errors (or "lapses") into account. Second, a number of goodness-of-fit tests are introduced. Because psychophysical data sets are usually rather small I advocate the use of Monte Carlo resampling techniques that do not rely on asymptotic theory for goodness-of-fit assessment. Third, a parametric bootstrap is employed to estimate the variability of fitted parameters and derived quantities such as thresholds and slopes. I describe how the bootstrap bridging assumption, on which the validity of the procedure depends, can be tested without incurring too high a cost in computation time. Finally I describe how the methods can be extended to test hypotheses concerning the form and shape of several psychometric functions. Software describing the methods is available (http://www.bootstrap-software.com/psignifit/), as well as articles describing the methods in detail (Wichmann&Hill, Perception&Psychophysics, 2001a,b).

ei

[BibTex]

[BibTex]


no image
A kernel approach for learning from almost orthogonal patterns

Schölkopf, B., Weston, J., Eskin, E., Leslie, C., Noble, W.

In Principles of Data Mining and Knowledge Discovery, Lecture Notes in Computer Science, 2430/2431, pages: 511-528, Lecture Notes in Computer Science, (Editors: T Elomaa and H Mannila and H Toivonen), Springer, Berlin, Germany, 13th European Conference on Machine Learning (ECML) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'2002), 2002 (inproceedings)

ei

PostScript DOI [BibTex]

PostScript DOI [BibTex]


no image
Optimal linear estimation of self-motion - a real-world test of a model of fly tangential neurons

Franz, MO.

SAB 02 Workshop, Robotics as theoretical biology, 7th meeting of the International Society for Simulation of Adaptive Behaviour (SAB), (Editors: Prescott, T.; Webb, B.), 2002 (poster)

Abstract
The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion (see example in Fig.1). We examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge both about the distance distribution of the environment, and about the noise and self-motion statistics of the sensor. The optimal estimator is tested on a gantry carrying an omnidirectional vision sensor that can be moved along three translational and one rotational degree of freedom. The experiments indicate that the proposed approach yields accurate results for rotation estimates, independently of the current translation and scene layout. Translation estimates, however, turned out to be sensitive to simultaneous rotation and to the particular distance distribution of the scene. The gantry experiments confirm that the receptive field organization of the tangential neurons allows them, as an ensemble, to extract self-motion from the optic flow.

ei

PDF [BibTex]

PDF [BibTex]


no image
Luminance Artifacts on CRT Displays

Wichmann, F.

In IEEE Visualization, pages: 571-574, (Editors: Moorhead, R.; Gross, M.; Joy, K. I.), IEEE Visualization, 2002 (inproceedings)

Abstract
Most visualization panels today are still built around cathode-ray tubes (CRTs), certainly on personal desktops at work and at home. Whilst capable of producing pleasing images for common applications ranging from email writing to TV and DVD presentation, it is as well to note that there are a number of nonlinear transformations between input (voltage) and output (luminance) which distort the digital and/or analogue images send to a CRT. Some of them are input-independent and hence easy to fix, e.g. gamma correction, but others, such as pixel interactions, depend on the content of the input stimulus and are thus harder to compensate for. CRT-induced image distortions cause problems not only in basic vision research but also for applications where image fidelity is critical, most notably in medicine (digitization of X-ray images for diagnostic purposes) and in forms of online commerce, such as the online sale of images, where the image must be reproduced on some output device which will not have the same transfer function as the customer's CRT. I will present measurements from a number of CRTs and illustrate how some of their shortcomings may be problematic for the aforementioned applications.

ei

[BibTex]

[BibTex]


no image
Learning rhythmic movements by demonstration using nonlinear oscillators

Ijspeert, J. A., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), pages: 958-963, Piscataway, NJ: IEEE, Lausanne, Sept.30-Oct.4 2002, 2002, clmc (inproceedings)

Abstract
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.

am

link (url) [BibTex]

link (url) [BibTex]


no image
Pressure Isotherms of Hydrogen Adsorption in Carbon Nanostructures

Chen, X., Dettlaff-Weglikowska, U., Haluska, M., Hulman, M., Roth, S., Hirscher, M., Becher, M.

In Making Functional Materials with Nanotubes, pages: Z9.11.1-Z9.11.6, Materials Research Society Symposium Proceedings, MRS, Boston [Mass.], 2002 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Hydrogen Storage in Carbon SWNTs: Atomic or Molecular?

Haluska, M., Hirscher, M., Becher, M., Dettlaff-Weglikowska, U., Chen, X., Roth, S.

In Structural and Electronic Properties of Molecular Nanostructures, pages: 601-605, AIP Conference Proceedings, AIP, Kirchberg, Tirol [Austria], 2002 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Hydrogen Storage in Nanostructured Carbon Materials at Room Temperature

Chen, X., Dettlaff-Weglikowska, U., Haluska, M., Hirscher, M., Becher, M., Roth, S.

In Structural and Electronic Properties of Molecular Nanostructures, pages: 597-600, AIP Conference Proceedings, AIP, Kirchberg, Tirol [Austria], 2002 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Movement imitation with nonlinear dynamical systems in humanoid robots

Ijspeert, J. A., Nakanishi, J., Schaal, S.

In International Conference on Robotics and Automation (ICRA2002), Washinton, May 11-15 2002, 2002, clmc (inproceedings)

Abstract
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.

am

link (url) [BibTex]

link (url) [BibTex]


no image
A locally weighted learning composite adaptive controller with structure adaptation

Nakanishi, J., Farrell, J. A., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), Lausanne, Sept.30-Oct.4 2002, 2002, clmc (inproceedings)

Abstract
This paper introduces a provably stable adaptive learning controller which employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator. This paper introduces a provably stable adaptive learning controller which employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator

am

link (url) [BibTex]

link (url) [BibTex]


no image
Nanomolding based fabrication of synthetic gecko foot-hairs

Sitti, M., Fearing, R. S.

In Nanotechnology, 2002. IEEE-NANO 2002. Proceedings of the 2002 2nd IEEE Conference on, pages: 137-140, 2002 (inproceedings)

pi

Project Page [BibTex]

Project Page [BibTex]


no image
Micromagnetism and the microstructure of the cell walls in Sm2Co17 based permanent magnets

Goll, D., Hadjipanayis, G. C., Kronmüller, H.

In Proceedings of the 17th International Workshop on Rare-Earth Magnets and their Applications, pages: 696-703, Rinton Press, Newark, Delaware, USA, 2002 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Ab-initio study of the influence of epitaxial strain on magnetoelastic properties

Komelj, M., Fähnle, M.

In Atomistic Aspects of Epitaxial Growth, pages: 439-447, NATO Science series: Series 2, Mathematics, Physics, and Chemistry, Kluwer Academic Publishers, Dassia, Corfu [Greece], 2002 (inproceedings)

mms

[BibTex]

[BibTex]

2001


no image
Unsupervised Segmentation and Classification of Mixtures of Markovian Sources

Seldin, Y., Bejerano, G., Tishby, N.

In The 33rd Symposium on the Interface of Computing Science and Statistics (Interface 2001 - Frontiers in Data Mining and Bioinformatics), pages: 1-15, 33rd Symposium on the Interface of Computing Science and Statistics (Interface - Frontiers in Data Mining and Bioinformatics), 2001 (inproceedings)

Abstract
We describe a novel algorithm for unsupervised segmentation of sequences into alternating Variable Memory Markov sources, first presented in [SBT01]. The algorithm is based on competitive learning between Markov models, when implemented as Prediction Suffix Trees [RST96] using the MDL principle. By applying a model clustering procedure, based on rate distortion theory combined with deterministic annealing, we obtain a hierarchical segmentation of sequences between alternating Markov sources. The method is applied successfully to unsupervised segmentation of multilingual texts into languages where it is able to infer correctly both the number of languages and the language switching points. When applied to protein sequence families (results of the [BSMT01] work), we demonstrate the method‘s ability to identify biologically meaningful sub-sequences within the proteins, which correspond to signatures of important functional sub-units called domains. Our approach to proteins classification (through the obtained signatures) is shown to have both conceptual and practical advantages over the currently used methods.

ei

PDF Web [BibTex]

2001


PDF Web [BibTex]


no image
Unsupervised Sequence Segmentation by a Mixture of Switching Variable Memory Markov Sources

Seldin, Y., Bejerano, G., Tishby, N.

In In the proceeding of the 18th International Conference on Machine Learning (ICML 2001), pages: 513-520, 18th International Conference on Machine Learning (ICML), 2001 (inproceedings)

Abstract
We present a novel information theoretic algorithm for unsupervised segmentation of sequences into alternating Variable Memory Markov sources. The algorithm is based on competitive learning between Markov models, when implemented as Prediction Suffix Trees (Ron et al., 1996) using the MDL principle. By applying a model clustering procedure, based on rate distortion theory combined with deterministic annealing, we obtain a hierarchical segmentation of sequences between alternating Markov sources. The algorithm seems to be self regulated and automatically avoids over segmentation. The method is applied successfully to unsupervised segmentation of multilingual texts into languages where it is able to infer correctly both the number of languages and the language switching points. When applied to protein sequence families, we demonstrate the method‘s ability to identify biologically meaningful sub-sequences within the proteins, which correspond to important functional sub-units called domains.

ei

PDF [BibTex]

PDF [BibTex]


no image
Inference Principles and Model Selection

Buhmann, J., Schölkopf, B.

(01301), Dagstuhl Seminar, 2001 (techreport)

ei

Web [BibTex]

Web [BibTex]


no image
Survey of nanomanipulation systems

Sitti, M.

In Nanotechnology, 2001. IEEE-NANO 2001. Proceedings of the 2001 1st IEEE Conference on, pages: 75-80, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Nanotribological characterization system by AFM based controlled pushing

Sitti, M.

In Nanotechnology, 2001. IEEE-NANO 2001. Proceedings of the 2001 1st IEEE Conference on, pages: 99-104, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Humanoid oculomotor control based on concepts of computational neuroscience

Shibata, T., Vijayakumar, S., Conradt, J., Schaal, S.

In Humanoids2001, Second IEEE-RAS International Conference on Humanoid Robots, 2001, clmc (inproceedings)

Abstract
Oculomotor control in a humanoid robot faces similar problems as biological oculomotor systems, i.e., the stabilization of gaze in face of unknown perturbations of the body, selective attention, the complexity of stereo vision and dealing with large information processing delays. In this paper, we suggest control circuits to realize three of the most basic oculomotor behaviors - the vestibulo-ocular and optokinetic reflex (VOR-OKR) for gaze stabilization, smooth pursuit for tracking moving objects, and saccades for overt visual attention. Each of these behaviors was derived from inspirations from computational neuroscience, which proves to be a viable strategy to explore novel control mechanisms for humanoid robotics. Our implementations on a humanoid robot demonstrate good performance of the oculomotor behaviors that appears natural and human-like.

am

link (url) [BibTex]

link (url) [BibTex]


no image
Computational micromagnetism of magnetic structures and magnetization processes in thin plantelets and small particles

Kronmüller, H., Hertel, R.

In Magnetic Storage Sstems Beyond 2000, 41, pages: 345-362, Nato Science Series II: Mathematics, Physics and Chemistry, Kluwer Academic Publishers, Rhodos, Greece, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Hydrogen storage in mechanically treated single wall carbon nanotrubes

Haluska, M., Hulman, M., Hirscher, M., Becher, M., Roth, S., Stepanek, I., Bernier, P.

In Electronic Properties of Molecular Nanostructures: XV International Winterschool/Euroconference, 591, pages: 603-608, American Institute of Physics Conference Proceedings, AIP, Kirchberg [Austria], 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Isotopic mass and lattice constant of Si and Ge: X-Ray standing wave measurements

Zegenhagen, J., Kazimirov, A., Cao, L. X., Konuma, M., Sozontov, E., Plachke, D., Carstanjen, H. D., Bilger, G., Haller, E., Kohn, V., Cardona, M.

In Proceedings of the 25th Conference on the Physics of Semiconductors, 87, pages: 125-127, Springer proceedings in physics, Springer, Osaka, Japan, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Positron Annihilation Studies on Stable and Undercooled Metal Melts at the Stuttgart Pelletron

Stoll, H., Siegle, A., Major, J.

In Application of Accelerators in Research and Industry, 576, pages: 749-752, AIP Conference Proceedings, Denton, Texas, USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Towards flapping wing control for a micromechanical flying insect

Yan, J., Wood, R. J., Avadhanula, S., Sitti, M., Fearing, R. S.

In Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on, 4, pages: 3901-3908, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Man-machine interface for micro/nano manipulation with an afm probe

Aruk, B., Hashimoto, H., Sitti, M.

In Nanotechnology, 2001. IEEE-NANO 2001. Proceedings of the 2001 1st IEEE Conference on, pages: 151-156, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Trajectory formation for imitation with nonlinear dynamical systems

Ijspeert, A., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), pages: 752-757, Weilea, Hawaii, Oct.29-Nov.3, 2001, clmc (inproceedings)

Abstract
This article explores a new approach to learning by imitation and trajectory formation by representing movements as mixtures of nonlinear differential equations with well-defined attractor dynamics. An observed movement is approximated by finding a best fit of the mixture model to its data by a recursive least squares regression technique. In contrast to non-autonomous movement representations like splines, the resultant movement plan remains an autonomous set of nonlinear differential equations that forms a control policy which is robust to strong external perturbations and that can be modified by additional perceptual variables. This movement policy remains the same for a given target, regardless of the initial conditions, and can easily be re-used for new targets. We evaluate the trajectory formation system (TFS) in the context of a humanoid robot simulation that is part of the Virtual Trainer (VT) project, which aims at supervising rehabilitation exercises in stroke-patients. A typical rehabilitation exercise was collected with a Sarcos Sensuit, a device to record joint angular movement from human subjects, and approximated and reproduced with our imitation techniques. Our results demonstrate that multi-joint human movements can be encoded successfully, and that this system allows robust modifications of the movement policy through external variables.

am

link (url) [BibTex]

link (url) [BibTex]


no image
Real-time statistical learning for robotics and human augmentation

Schaal, S., Vijayakumar, S., D’Souza, A., Ijspeert, A., Nakanishi, J.

In International Symposium on Robotics Research, (Editors: Jarvis, R. A.;Zelinsky, A.), Lorne, Victoria, Austrialia Nov.9-12, 2001, clmc (inproceedings)

Abstract
Real-time modeling of complex nonlinear dynamic processes has become increasingly important in various areas of robotics and human augmentation. To address such problems, we have been developing special statistical learning methods that meet the demands of on-line learning, in particular the need for low computational complexity, rapid learning, and scalability to high-dimensional spaces. In this paper, we introduce a novel algorithm that possesses all the necessary properties by combining methods from probabilistic and nonparametric learning. We demonstrate the applicability of our methods for three different applications in humanoid robotics, i.e., the on-line learning of a full-body inverse dynamics model, an inverse kinematics model, and imitation learning. The latter application will also introduce a novel method to shape attractor landscapes of dynamical system by means of statis-tical learning.

am

link (url) [BibTex]

link (url) [BibTex]


no image
Submicrometer spatially resolved measurements of mechanical properties and correlation to microstructure and composition

Kunert, M., Baretzky, B., Baker, S. P., Mittemeijer, E. J.

In Fundamentals of Nanoindentation and Nanotribology II, 649, pages: Q3.2.1-Q3.2.6, Materials Research Society Symposium Proceedings, MRS, Boston, MA, USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
The six-jump diffusion cycles in B2-compounds

Drautz, R., Meyer, B., Fähnle, M.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, pages: 417-422, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Ionic nitriding of austenitic and ferritic steel with the aid of a high aperture hall current accelerator

Straumal, B. B., Vershinin, N. F., Friesel, M., Ishenko, S. A., Gust, W.

In Diffusion in Materials DIMAT2000, 194, pages: 1457-1462, Defect and Diffusion Forum, Trans Tech, Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Robust learning of arm trajectories through human demonstration

Billard, A., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), Piscataway, NJ: IEEE, Maui, Hawaii, Oct.29-Nov.3, 2001, clmc (inproceedings)

Abstract
We present a model, composed of hierarchy of artificial neural networks, for robot learning by demonstration. The model is implemented in a dynamic simulation of a 41 degrees of freedom humanoid for reproducing 3D human motion of the arm. Results show that the model requires few information about the desired trajectory and learns on-line the relevant features of movement. It can generalize across a small set of data to produce a qualitatively good reproduction of the demonstrated trajectory. Finally, it is shown that reproduction of the trajectory after learning is robust against perturbations.

am

link (url) [BibTex]

link (url) [BibTex]


no image
Development of PZT and PZN-PT based unimorph actuators for micromechanical flapping mechanisms

Sitti, M., Campolo, D., Yan, J., Fearing, R. S.

In Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on, 4, pages: 3839-3846, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Thorax Design and Wing Control for a Micromechanical Flying Insect

Yan, J, Ayadhanula, S, Sitti, M, Wood, RJ, Fearing, RS

In PROCEEDINGS OF THE ANNUAL ALLERTON CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING, 39(2):952-961, 2001 (inproceedings)

pi

[BibTex]

[BibTex]


no image
First proof of slow trapping of positronium in polymers by an Age-Momentum-Correlation (AMOC) experiment

Dauwe, C., Balcaen, N., van Waeyenberge, B., van Petegem, S., Stoll, H.

In Positron Annihilation. Proceedings of the 12th International Conference on Positron Annihilation, 363/365, pages: 254-256, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Positron-age-momentum correlation

Stoll, H., Bandzuch, P., Siegle, A.

In Positron Annihilation: Proceedings of the 12th International Conference on Positron Annihilation, 363-365, pages: 547-551, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Nanocrystalline and nanostructured high-performance permanent magnets

Goll, D., Hadjipanayis, G. C., Kronmüller, H.

In Applications of Ferromagnetic and Optical Materials, Storage and Magnetoelectronics, 674, pages: U2.4.1-U2.4.12, Materials Research Society Symposium Proceedings, MRS, San Francisco, Calif., 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
Ion beam analysis with monolayer depth resolution using the electrostatic spectrometer at the MPI Stuttgart

Plachke, D., Blohm, G., Fischer, T., Khellaf, A., Kruse, O., Stoll, H., Carstanjen, H. D.

In Proceedings of the 16th International Conference on Applications of Accelerators in Research and Industry, 576, pages: 458-462, American Institute of Physics Conference Proceedings, AIP, Denton, Texas, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


no image
From the electronic structure to the macroscopiy behavior: A multi-scale analysis of plasticity in intermetallic compounds

Fähnle, M., Kohlhammer, S., Bester, G.

In Influences of Interface and Dislocation Behavior on Microstructure Evolution, 652, pages: Y4.5.1.-Y4.5.12, Materials Research Society Symposium Proceedings, MRS, Boston, Mass., USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]