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2002


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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]

2002


PDF PDF DOI [BibTex]


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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]


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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]


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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]


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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]


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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]


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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]


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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]


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Untersuchungen zur Spindynamik in nanostrukturierten ferromagnetischen Schichtsystemen

Puzic, A.

Universität Stuttgart, Stuttgart, 2002 (mastersthesis)

mms

[BibTex]

[BibTex]


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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]


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Magnetic Imaging of Nanostructured Systems with Transmission X-Ray Microscopy

Eimüller, T.

Bayrische Julius-Maximilians-Universität Würzburg, Würzburg, 2002 (phdthesis)

mms

[BibTex]

[BibTex]


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Ab-initio Berechnung der Spinwellenspektren von Eisen, Kobalt und Nickel

Grotheer, O.

Universität Stuttgart, Stuttgart, 2002 (phdthesis)

mms

[BibTex]

[BibTex]


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Kernspinresonanzuntersuchungen zur Diffusion von Wasserstoff in kubischen Lavesphasen

Eberle, U.

Universität Stuttgart, Stuttgart, 2002 (phdthesis)

mms

[BibTex]

[BibTex]


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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]


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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]


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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]


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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]


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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]


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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]

1999


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Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites in DNA

Zien, A., Rätsch, G., Mika, S., Schölkopf, B., Lemmen, C., Smola, A., Lengauer, T., Müller, K.

In German Conference on Bioinformatics (GCB 1999), October 1999 (inproceedings)

Abstract
In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points from which regions encoding pro­ teins start, the so­called translation initiation sites (TIS). This can be modeled as a classification prob­ lem. We demonstrate the power of support vector machines (SVMs) for this task, and show how to suc­ cessfully incorporate biological prior knowledge by engineering an appropriate kernel function.

ei

Web [BibTex]

1999


Web [BibTex]


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Tele-touch feedback of surfaces at the micro/nano scale: Modeling and experiments

Sitti, M., Horighuchi, S., Hashimoto, H.

In Intelligent Robots and Systems, 1999. IROS’99. Proceedings. 1999 IEEE/RSJ International Conference on, 2, pages: 882-888, 1999 (inproceedings)

pi

[BibTex]

[BibTex]


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Challenge to micro/nanomanipulation using atomic force microscope

Hashimoto, H., Sitti, M.

In Micromechatronics and Human Science, 1999. MHS’99. Proceedings of 1999 International Symposium on, pages: 35-42, 1999 (inproceedings)

pi

[BibTex]

[BibTex]


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Visualization interface for AFM-based nano-manipulation

Horiguchi, S., Sitti, M., Hashimoto, H.

In Industrial Electronics, 1999. ISIE’99. Proceedings of the IEEE International Symposium on, 1, pages: 310-315, 1999 (inproceedings)

pi

[BibTex]

[BibTex]


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Tele-nanorobotics 2-d manipulation of micro/nanoparticles using afm

Sitti, M., Horiguchi, S., Hashimoto, H.

In Advanced Intelligent Mechatronics, 1999. Proceedings. 1999 IEEE/ASME International Conference on, pages: 786-786, 1999 (inproceedings)

pi

[BibTex]

[BibTex]


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Two-dimensional fine particle positioning using a piezoresistive cantilever as a micro/nano-manipulator

Sitti, M., Hashimoto, H.

In Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on, 4, pages: 2729-2735, 1999 (inproceedings)

pi

[BibTex]

[BibTex]

1996


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A kendama learning robot based on a dynamic optimiation principle

Miyamoto, H., Gandolfo, F., Gomi, H., Schaal, S., Koike, Y., Rieka, O., Nakano, E., Wada, Y., Kawato, M.

In Preceedings of the International Conference on Neural Information Processing, pages: 938-942, Hong Kong, September 1996, clmc (inproceedings)

am

[BibTex]

1996


[BibTex]


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Incorporating invariances in support vector learning machines

Schölkopf, B., Burges, C., Vapnik, V.

In Artificial Neural Networks: ICANN 96, LNCS vol. 1112, pages: 47-52, (Editors: C von der Malsburg and W von Seelen and JC Vorbrüggen and B Sendhoff), Springer, Berlin, Germany, 6th International Conference on Artificial Neural Networks, July 1996, volume 1112 of Lecture Notes in Computer Science (inproceedings)

Abstract
Developed only recently, support vector learning machines achieve high generalization ability by minimizing a bound on the expected test error; however, so far there existed no way of adding knowledge about invariances of a classification problem at hand. We present a method of incorporating prior knowledge about transformation invariances by applying transformations to support vectors, the training examples most critical for determining the classification boundary.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Geometric Image Synthesis

Alhaija, H. A., Mustikovela, S. K., Geiger, A., Rother, C.

(conference)

avg

Project Page [BibTex]

Project Page [BibTex]