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3447 results (BibTeX)

1998


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Eine beweistheoretische Anwendung der

Harmeling, S.

Biologische Kybernetik, Westfälische Wilhelms-Universität Münster, Münster, May 1998 (diplomathesis)

ei

PDF [BibTex]

1998


PDF [BibTex]


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On a Kernel-Based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion

Smola, A., Schölkopf, B.

Algorithmica, 22(1-2):211-231, September 1998 (article)

Abstract
We present a kernel-based framework for pattern recognition, regression estimation, function approximation, and multiple operator inversion. Adopting a regularization-theoretic framework, the above are formulated as constrained optimization problems. Previous approaches such as ridge regression, support vector methods, and regularization networks are included as special cases. We show connections between the cost function and some properties up to now believed to apply to support vector machines only. For appropriately chosen cost functions, the optimal solution of all the problems described above can be found by solving a simple quadratic programming problem.

ei

PDF DOI [BibTex]


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The connection between regularization operators and support vector kernels.

Smola, A., Schölkopf, B., Müller, K.

Neural Networks, 11(4):637-649, June 1998 (article)

Abstract
n this paper a correspondence is derived between regularization operators used in regularization networks and support vector kernels. We prove that the Green‘s Functions associated with regularization operators are suitable support vector kernels with equivalent regularization properties. Moreover, the paper provides an analysis of currently used support vector kernels in the view of regularization theory and corresponding operators associated with the classes of both polynomial kernels and translation invariant kernels. The latter are also analyzed on periodical domains. As a by-product we show that a large number of radial basis functions, namely conditionally positive definite functions, may be used as support vector kernels.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Programmable pattern generators

Schaal, S., Sternad, D.

In 3rd International Conference on Computational Intelligence in Neuroscience, pages: 48-51, Research Triangle Park, NC, Oct. 24-28, October 1998, clmc (inproceedings)

Abstract
This paper explores the idea to create complex human-like arm movements from movement primitives based on nonlinear attractor dynamics. Each degree-of-freedom of an arm is assumed to have two independent abilities to create movement, one through a discrete dynamic system, and one through a rhythmic system. The discrete system creates point-to-point movements based on internal or external target specifications. The rhythmic system can add an additional oscillatory movement relative to the current position of the discrete system. In the present study, we develop appropriate dynamic systems that can realize the above model, motivate the particular choice of the systems from a biological and engineering point of view, and present simulation results of the performance of such movement primitives. Implementation results on a Sarcos Dexterous Arm are discussed.

am

link (url) [BibTex]

link (url) [BibTex]


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PET with 18fluorodeoxyglucose and hexamethylpropylene amine oxime SPECT in late whiplash syndrome

Bicik, I., Radanov, B., Schaefer, N., Dvorak, J., Blum, B., Weber, B., Burger, C., von Schulthess, G., Buck, A.

Neurology, 51, pages: 345-350, 1998 (article)

ei

[BibTex]

[BibTex]


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Changes of cerebral blood flow during short-term exposure to normobaric hypoxia

Buck, A., Schirlo, C., Jasinsky, V., Weber, B., Burger, C., von Schulthess, G., Koller, E., Pavlicek, V.

J Cereb Blood Flow Metab, 18, pages: 906-910, 1998 (article)

ei

[BibTex]

[BibTex]


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Kernel PCA pattern reconstruction via approximate pre-images.

Schölkopf, B., Mika, S., Smola, A., Rätsch, G., Müller, K.

In 8th International Conference on Artificial Neural Networks, pages: 147-152, Perspectives in Neural Computing, (Editors: L Niklasson and M Boden and T Ziemke), Springer, Berlin, Germany, 8th International Conference on Artificial Neural Networks, 1998 (inproceedings)

ei

[BibTex]

[BibTex]


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Generalization Bounds for Convex Combinations of Kernel Functions

Smola, A., Williamson, R., Schölkopf, B.

Royal Holloway College, 1998 (techreport)

ei

[BibTex]

[BibTex]


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Generalization Performance of Regularization Networks and Support Vector Machines via Entropy Numbers of Compact Operators

Williamson, R., Smola, A., Schölkopf, B.

(19), NeuroCOLT, 1998, Accepted for publication in IEEE Transactions on Information Theory (techreport)

ei

[BibTex]

[BibTex]


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A bootstrap method for testing hypotheses concerning psychometric functions

Hill, N., Wichmann, F.

1998 (poster)

Abstract
Whenever psychometric functions are used to evaluate human performance on some task, it is valuable to examine not only the threshold and slope values estimated from the original data, but also the expected variability in those measures. This allows psychometric functions obtained in two experimental conditions to be compared statistically. We present a method for estimating the variability of thresholds and slopes of psychometric functions. This involves a maximum-likelihood fit to the data using a three-parameter mathematical function, followed by Monte Carlo simulation using the first fit as a generating function for the simulations. The variability of the function's parameters can then be estimated (as shown by Maloney, 1990), as can the variability of the threshold value (Foster & Bischof, 1997). We will show how a simple development of this procedure can be used to test the significance of differences between (a) the thresholds, and (b) the slopes of two psychometric functions. Further, our method can be used to assess the assumptions underlying the original fit, by examining how goodness-of-fit differs in simulation from its original value. In this way data sets can be identified as being either too noisy to be generated by a binomial observer, or significantly "too good to be true." All software is written in MATLAB and is therefore compatible across platforms, with the option of accelerating performance using MATLAB's plug-in binaries, or "MEX" files.

ei

[BibTex]


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Prior knowledge in support vector kernels

Schölkopf, B., Simard, P., Smola, A., Vapnik, V.

In Advances in Neural Information Processing Systems 10, pages: 640-646 , (Editors: M Jordan and M Kearns and S Solla ), MIT Press, Cambridge, MA, USA, Eleventh Annual Conference on Neural Information Processing (NIPS), June 1998 (inproceedings)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Qualitative Modeling for Data Miner’s Requirements

Shin, H., Jhee, W.

In Proc. of the Korean Management Information Systems, pages: 65-73, Conference on the Korean Management Information Systems, April 1998 (inproceedings)

ei

[BibTex]

[BibTex]


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Quantization Functionals and Regularized PrincipalManifolds

Smola, A., Mika, S., Schölkopf, B.

NeuroCOLT, 1998, NC2-TR-1998-028 (techreport)

ei

[BibTex]

[BibTex]


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Support Vector Machines for Image Classification

Chapelle, O.

Biologische Kybernetik, Ecole Normale Superieure de Lyon, 1998 (diplomathesis)

ei

GZIP [BibTex]

GZIP [BibTex]


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Qualitative Modeling for Data Miner‘s Requirement

Shin, H.

Biologische Kybernetik, Hong-Ik University, Seoul, Korea, February 1998, Written in Korean (diplomathesis)

ei

ZIP [BibTex]

ZIP [BibTex]


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Navigation mit Schnappschüssen

Franz, M., Schölkopf, B., Mallot, H., Bülthoff, H., Zell, A.

In Mustererkennung 1998, pages: 421-428, (Editors: P Levi and R-J Ahlers and F May and M Schanz), Springer, Berlin, Germany, 20th DAGM-Symposium, October 1998 (inproceedings)

Abstract
Es wird ein biologisch inspirierter Algorithmus vorgestellt, mit dem sich ein Ort wiederfinden l{\"a}sst, an dem vorher eine 360-Grad-Ansicht der Umgebung aufgenommen wurde. Die Zielrichtung wird aus der Verschiebung der Bildposition der umgebenden Landmarken im Vergleich zum Schnappschuss berechnet. Die Konvergenzeigenschaften des Algorithmus werden mathematisch untersucht und auf mobilen Robotern getestet.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Local dimensionality reduction

Schaal, S., Vijayakumar, S., Atkeson, C. G.

In Advances in Neural Information Processing Systems 10, pages: 633-639, (Editors: Jordan, M. I.;Kearns, M. J.;Solla, S. A.), MIT Press, Cambridge, MA, 1998, clmc (inproceedings)

Abstract
If globally high dimensional data has locally only low dimensional distributions, it is advantageous to perform a local dimensionality reduction before further processing the data. In this paper we examine several techniques for local dimensionality reduction in the context of locally weighted linear regression. As possible candidates, we derive local versions of factor analysis regression, principle component regression, principle component regression on joint distributions, and partial least squares regression. After outlining the statistical bases of these methods, we perform Monte Carlo simulations to evaluate their robustness with respect to violations of their statistical assumptions. One surprising outcome is that locally weighted partial least squares regression offers the best average results, thus outperforming even factor analysis, the theoretically most appealing of our candidate techniques.

am

link (url) [BibTex]

link (url) [BibTex]


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From regularization operators to support vector kernels

Smola, A., Schölkopf, B.

In Advances in Neural Information Processing Systems 10, pages: 343-349, (Editors: M Jordan and M Kearns and S Solla), MIT Press, Cambridge, MA, USA, 11th Annual Conference on Neural Information Processing (NIPS), June 1998 (inproceedings)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Where did I take that snapshot? Scene-based homing by image matching

Franz, M., Schölkopf, B., Bülthoff, H.

Biological Cybernetics, 79(3):191-202, October 1998 (article)

Abstract
In homing tasks, the goal is often not marked by visible objects but must be inferred from the spatial relation to the visual cues in the surrounding scene. The exact computation of the goal direction would require knowledge about the distances to visible landmarks, information, which is not directly available to passive vision systems. However, if prior assumptions about typical distance distributions are used, a snapshot taken at the goal suffices to compute the goal direction from the current view. We show that most existing approaches to scene-based homing implicitly assume an isotropic landmark distribution. As an alternative, we propose a homing scheme that uses parameterized displacement fields. These are obtained from an approximation that incorporates prior knowledge about perspective distortions of the visual environment. A mathematical analysis proves that both approximations do not prevent the schemes from approaching the goal with arbitrary accuracy, but lead to different errors in the computed goal direction. Mobile robot experiments are used to test the theoretical predictions and to demonstrate the practical feasibility of the new approach.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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Constructive incremental learning from only local information

Schaal, S., Atkeson, C. G.

Neural Computation, 10(8):2047-2084, 1998, clmc (article)

Abstract
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, the size and shape of the receptive field of each locally linear model as well as the parameters of the locally linear model itself are learned independently, i.e., without the need for competition or any other kind of communication. Independent learning is accomplished by incrementally minimizing a weighted local cross validation error. As a result, we obtain a learning system that can allocate resources as needed while dealing with the bias-variance dilemma in a principled way. The spatial localization of the linear models increases robustness towards negative interference. Our learning system can be interpreted as a nonparametric adaptive bandwidth smoother, as a mixture of experts where the experts are trained in isolation, and as a learning system which profits from combining independent expert knowledge on the same problem. This paper illustrates the potential learning capabilities of purely local learning and offers an interesting and powerful approach to learning with receptive fields. 

am

link (url) [BibTex]

link (url) [BibTex]


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Biomimetic gaze stabilization based on a study of the vestibulocerebellum

Shibata, T., Schaal, S.

In European Workshop on Learning Robots, pages: 84-94, Edinburgh, UK, 1998, clmc (inproceedings)

Abstract
Accurate oculomotor control is one of the essential pre-requisites for successful visuomotor coordination. In this paper, we suggest a biologically inspired control system for learning gaze stabilization with a biomimetic robotic oculomotor system. In a stepwise fashion, we develop a control circuit for the vestibulo-ocular reflex (VOR) and the opto-kinetic response (OKR), and add a nonlinear learning network to allow adaptivity. We discuss the parallels and differences of our system with biological oculomotor control and suggest solutions how to deal with nonlinearities and time delays in the control system. In simulation and actual robot studies, we demonstrate that our system can learn gaze stabilization in real time in only a few seconds with high final accuracy.

am

link (url) [BibTex]

link (url) [BibTex]


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Book Review: An Introduction to Fuzzy Logic for Practical Applications

Peters, J.

K{\"u}nstliche Intelligenz (KI), 98(4):60-60, November 1998 (article)

ei

[BibTex]

[BibTex]


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Support vector machines

Hearst, M., Dumais, S., Osman, E., Platt, J., Schölkopf, B.

IEEE Intelligent Systems and their Applications, 13(4):18-28, July 1998 (article)

Abstract
My first exposure to Support Vector Machines came this spring when heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue's collection of essays should help familiarize our readers with this interesting new racehorse in the Machine Learning stable. Bernhard Scholkopf, in an introductory overview, points out that a particular advantage of SVMs over other learning algorithms is that it can be analyzed theoretically using concepts from computational learning theory, and at the same time can achieve good performance when applied to real problems. Examples of these real-world applications are provided by Sue Dumais, who describes the aforementioned text-categorization problem, yielding the best results to date on the Reuters collection, and Edgar Osuna, who presents strong results on application to face detection. Our fourth author, John Platt, gives us a practical guide and a new technique for implementing the algorithm efficiently.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Support Vector methods in learning and feature extraction

Schölkopf, B., Smola, A., Müller, K., Burges, C., Vapnik, V.

Ninth Australian Conference on Neural Networks, pages: 72-78, (Editors: T. Downs, M. Frean and M. Gallagher), 1998 (talk)

ei

[BibTex]

[BibTex]


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Convex Cost Functions for Support Vector Regression

Smola, A., Schölkopf, B., Müller, K.

In 8th International Conference on Artificial Neural Networks, pages: 99-104, Perspectives in Neural Computing, (Editors: L Niklasson and M Boden and T Ziemke), Springer, Berlin, Germany, 8th International Conference on Artificial Neural Networks, 1998 (inproceedings)

ei

[BibTex]

[BibTex]


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Support-Vektor-Lernen

Schölkopf, B.

In Ausgezeichnete Informatikdissertationen 1997, pages: 135-150, (Editors: G Hotz and H Fiedler and P Gorny and W Grass and S Hölldobler and IO Kerner and R Reischuk), Teubner Verlag, Stuttgart, 1998 (inbook)

ei

[BibTex]

[BibTex]


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Nonlinearities and the pedestal effect

Wichmann, F., Henning, G., Ploghaus, A.

Perception, 27, pages: S86, 1998 (poster)

Abstract
Psychophysical and physiological evidence suggests that luminance patterns are independently analysed in "channels" responding to different bands of spatial frequency. There are, however, interactions among stimuli falling well outside the usual estimates of channels' bandwidths (Henning, Hertz, and Broadbent, (1975). Vision Res., 15, 887-899). We examined whether the masking results of Henning et al. are consistent with independent channels. We postulated, before the channels, a point non-linearity which would introduce distortion products that might produce the observed interactions between stimuli two octaves apart in spatial frequency. Standard 2-AFC masking experiments determined whether possible distortion products of a 4.185 c/deg masking sinusoid revealed their presence through effects on the detection of a sinusoidal signal at the frequency of the second harmonic of the masker-8.37 c/deg. The signal and masker were horizontally orientated and the signal was in-phase, out-of-phase, or in quadrature with the putative second-order distortion product of the masker. Significant interactions between signal and masker were observed: for a wide range of masker contrasts, signal detection was facilitated by the masking stimulus. However, the shapes of the functions relating detection performance to masker contrast, as well as the effects of relative phase, were inconsistent with the notion that distortion products were responsible for the interactions observed.

ei

[BibTex]

[BibTex]


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The moon tilt illusion

Schölkopf, B.

Perception, 27(10):1229-1232, August 1998 (article)

Abstract
Besides the familiar moon illusion [eg Hershenson, 1989 The Moon illusion (Hillsdale, NJ: Lawrence Erlbaum Associates)], wherein the moon appears bigger when it is close to the horizon, there is a less known illusion which causes the moon‘s illuminated side to appear turned away from the direction of the sun. An experiment documenting the effect is described, and a possible explanation is put forward.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Towards biomimetic vision

Shibata, T., Schaal, S.

In International Conference on Intelligence Robots and Systems, pages: 872-879, Victoria, Canada, 1998, clmc (inproceedings)

Abstract
Oculomotor control is the foundation of most biological visual systems, as well as an important component in the entire perceptual-motor system. We review some of the most basic principles of biological oculomotor systems, and explore their usefulness from both the biological and computational point of view. As an example of biomimetic oculomotor control, we present the state of our implementations and experimental results using the vestibulo-ocular-reflex and opto-kinetic-reflex paradigm

am

link (url) [BibTex]

link (url) [BibTex]


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Local adaptive subspace regression

Vijayakumar, S., Schaal, S.

Neural Processing Letters, 7(3):139-149, 1998, clmc (article)

Abstract
Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as biological movement systems. So far, due to sparsity of data in high dimensional spaces, learning in such settings requires a significant amount of prior knowledge about the learning task, usually provided by a human expert. In this paper we suggest a partial revision of the view. Based on empirical studies, we observed that, despite being globally high dimensional and sparse, data distributions from physical movement systems are locally low dimensional and dense. Under this assumption, we derive a learning algorithm, Locally Adaptive Subspace Regression, that exploits this property by combining a dynamically growing local dimensionality reduction technique  as a preprocessing step with a nonparametric learning technique, locally weighted regression, that also learns the region of validity of the regression. The usefulness of the algorithm and the validity of its assumptions are illustrated for a synthetic data set, and for data of the inverse dynamics of human arm movements and an actual 7 degree-of-freedom anthropomorphic robot arm. 

am

link (url) [BibTex]

link (url) [BibTex]


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Characterization of the oligomerization defects of two p53 mutants found in families with Li-Fraumeni and Li-Fraumeni-like syndrome.

Davison, T., Yin, P., Nie, E., Kay, C., CH, ..

Oncogene, 17(5):651-656, August 1998 (article)

Abstract
Recently two germline mutations in the oligomerization domain of p53 have been identified in patients with Li-Fraumeni and Li-Fraumeni-like Syndromes. We have used biophysical and biochemical methods to characterize these two mutants in order to better understand their functional defects and the role of the p53 oligomerization domain (residues 325-355) in oncogenesis. We find that residues 310-360 of the L344P mutant are monomeric, apparently unfolded and cannot interact with wild-type (WT) p53. The full length L344P protein is unable to bind sequence specifically to DNA and is therefore an inactive, but not a dominant negative mutant. R337C, on the other hand, can form dimers and tetramers, can hetero-oligomerize with WTp53 and can bind to a p53 consensus element. However, the thermal stability of R337C is much lower than that of WTp53 and at physiological temperatures more than half of this mutant is less than tetrameric. Thus, the R337C mutant retains some functional activity yet leads to a predisposition to cancer, suggesting that even partial inactivation of p53 oligomerization is sufficient for accelerated tumour progression.

ei

Web [BibTex]


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Funktionelle Magnetresonanztomographie in der psychopathologischen Forschung.

Spitzer, M., Kammer, T., Bellemann, M., Brix, G., Layer, B., Maier, S., Kischka, U., Gückel, F.

Fortschritte der Neurologie Psychiatrie, 66, pages: 241-258, 1998 (article)

Abstract
Mental disorders are characterised by psychopathological symptoms which correspond to functional brain states. Functional magnetic resonance imaging (fMRI) is used for the non-invasive study of cerebral activation patterns in man. First of all, the neurobiological principles and presuppositions of the method are outlined. Results from the Heidelberg imaging lab on several simple sensorimotor tasks as well as higher cognitive functions, such as working and semantic memory, are then presented. Thereafter, results from preliminary fMRI studies of psychopathological symptoms are discussed, with emphasis on hallucinations, psychomotoric phenomena, emotions, as well as obsessions and compulsions. Functional MRI is limited by the physics underlying the method, as well as by practical constraints regarding its use in conjunction with mentally ill patients. Within this framework, the problems of signal-to-noise ratio, data analysis strategies, motion correction, and neurovascular coupling are considered. Because of the rapid development of the field of fMRI, maps of higher cognitive functions and their respective pathology seem to be coming within easy reach.

ei

[BibTex]

[BibTex]


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Support vector regression with automatic accuracy control.

Schölkopf, B., Bartlett, P., Smola, A., Williamson, R.

In ICANN'98, pages: 111-116, Perspectives in Neural Computing, (Editors: L Niklasson and M Boden and T Ziemke), Springer, Berlin, Germany, International Conference on Artificial Neural Networks (ICANN'98), 1998 (inproceedings)

ei

[BibTex]

[BibTex]


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General cost functions for support vector regression.

Smola, A., Schölkopf, B., Müller, K.

In Ninth Australian Conference on Neural Networks, pages: 79-83, (Editors: T Downs and M Frean and M Gallagher), 9th Australian Conference on Neural Networks (ACNN'98), 1998 (inproceedings)

ei

[BibTex]

[BibTex]


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Asymptotically optimal choice of varepsilon-loss for support vector machines.

Smola, A., Murata, N., Schölkopf, B., Müller, K.

In 8th International Conference on Artificial Neural Networks, pages: 105-110, Perspectives in Neural Computing, (Editors: L Niklasson and M Boden and T Ziemke), Springer, Berlin, Germany, 8th International Conference on Artificial Neural Networks, 1998 (inproceedings)

ei

[BibTex]

[BibTex]


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Support Vector Machine Reference Manual

Saunders, C., Stitson, M., Weston, J., Bottou, L., Schölkopf, B., Smola, A.

(CSD-TR-98-03), Department of Computer Science, Royal Holloway, University of London, 1998 (techreport)

ei

PostScript [BibTex]

PostScript [BibTex]


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Übersicht durch Übersehen

Schölkopf, B.

Frankfurter Allgemeine Zeitung , Wissenschaftsbeilage, March 1998 (misc)

ei

[BibTex]

[BibTex]

1997


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Recognizing human motion using parameterized models of optical flow

Black, M. J., Yacoob, Y., Ju, X. S.

In Motion-Based Recognition, pages: 245-269, (Editors: Mubarak Shah and Ramesh Jain,), Kluwer Academic Publishers, Boston, MA, 1997 (incollection)

ps

pdf [BibTex]

1997


pdf [BibTex]


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Modeling appearance change in image sequences

Black, M. J., Yacoob, Y., Fleet, D. J.

In Advances in Visual Form Analysis, pages: 11-20, Proceedings of the Third International Workshop on Visual Form, Capri, Italy, May 1997 (inproceedings)

ps

abstract [BibTex]

abstract [BibTex]


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Robust anisotropic diffusion: Connections between robust statistics, line processing, and anisotropic diffusion

Black, M. J., Sapiro, G., Marimont, D., Heeger, D.

In Scale-Space Theory in Computer Vision, Scale-Space’97, pages: 323-326, LNCS 1252, Springer Verlag, Utrecht, the Netherlands, July 1997 (inproceedings)

ps

pdf [BibTex]

pdf [BibTex]


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Analysis of gesture and action in technical talks for video indexing

Ju, S. X., Black, M. J., Minneman, S., Kimber, D.

In IEEE Conf. on Computer Vision and Pattern Recognition, pages: 595-601, CVPR-97, Puerto Rico, June 1997 (inproceedings)

Abstract
In this paper, we present an automatic system for analyzing and annotating video sequences of technical talks. Our method uses a robust motion estimation technique to detect key frames and segment the video sequence into subsequences containing a single overhead slide. The subsequences are stabilized to remove motion that occurs when the speaker adjusts their slides. Any changes remaining between frames in the stabilized sequences may be due to speaker gestures such as pointing or writing and we use active contours to automatically track these potential gestures. Given the constrained domain we define a simple ``vocabulary'' of actions which can easily be recognized based on the active contour shape and motion. The recognized actions provide a rich annotation of the sequence that can be used to access a condensed version of the talk from a web page.

ps

pdf [BibTex]

pdf [BibTex]


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Learning parameterized models of image motion

Black, M. J., Yacoob, Y., Jepson, A. D., Fleet, D. J.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-97, pages: 561-567, Puerto Rico, June 1997 (inproceedings)

Abstract
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that are computed from a training set using principal component analysis. Many complex image motions can be represented by a linear combination of a small number of these basis flows. The learned motion models may be used for optical flow estimation and for model-based recognition. For optical flow estimation we describe a robust, multi-resolution scheme for directly computing the parameters of the learned flow models from image derivatives. As examples we consider learning motion discontinuities, non-rigid motion of human mouths, and articulated human motion.

ps

pdf [BibTex]

pdf [BibTex]


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Robust anisotropic diffusion and sharpening of scalar and vector images

Black, M. J., Sapiro, G., Marimont, D., Heeger, D.

In Int. Conf. on Image Processing, ICIP, 1, pages: 263-266, Vol. 1, Santa Barbara, CA, October 1997 (inproceedings)

Abstract
Relations between anisotropic diffusion and robust statistics are described. We show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edge-stopping" function in the anisotropic diffusion equation is closely related to the error norm and influence function in the robust estimation framework. This connection leads to a new "edge-stopping" function based on Tukey's biweight robust estimator, that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. The robust statistical interpretation also provides a means for detecting the boundaries (edges) between the piecewise smooth regions in the image. We extend the framework to vector-valued images and show applications to robust image sharpening.

ps

pdf publisher site [BibTex]

pdf publisher site [BibTex]


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Recognizing facial expressions in image sequences using local parameterized models of image motion

Black, M. J., Yacoob, Y.

Int. Journal of Computer Vision, 25(1):23-48, 1997 (article)

Abstract
This paper explores the use of local parametrized models of image motion for recovering and recognizing the non-rigid and articulated motion of human faces. Parametric flow models (for example affine) are popular for estimating motion in rigid scenes. We observe that within local regions in space and time, such models not only accurately model non-rigid facial motions but also provide a concise description of the motion in terms of a small number of parameters. These parameters are intuitively related to the motion of facial features during facial expressions and we show how expressions such as anger, happiness, surprise, fear, disgust, and sadness can be recognized from the local parametric motions in the presence of significant head motion. The motion tracking and expression recognition approach performed with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.

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pdf pdf from publisher abstract video [BibTex]


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Comparing support vector machines with Gaussian kernels to radial basis function classifiers

Schölkopf, B., Sung, K., Burges, C., Girosi, F., Niyogi, P., Poggio, T., Vapnik, V.

IEEE Transactions on Signal Processing, 45(11):2758-2765, November 1997 (article)

Abstract
The support vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights, and threshold that minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by X-means clustering, and the weights are computed using error backpropagation. We consider three machines, namely, a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the United States postal service database of handwritten digits, the SV machine achieves the highest recognition accuracy, followed by the hybrid system. The SV approach is thus not only theoretically well-founded but also superior in a practical application.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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The view-graph approach to visual navigation and spatial memory

Mallot, H., Franz, M., Schölkopf, B., Bülthoff, H.

In Artificial Neural Networks: ICANN ’97, pages: 751-756, (Editors: W Gerstner and A Germond and M Hasler and J-D Nicoud), Springer, Berlin, Germany, 7th International Conference on Artificial Neural Networks, October 1997 (inproceedings)

Abstract
This paper describes a purely visual navigation scheme based on two elementary mechanisms (piloting and guidance) and a graph structure combining individual navigation steps controlled by these mechanisms. In robot experiments in real environments, both mechanisms have been tested, piloting in an open environment and guidance in a maze with restricted movement opportunities. The results indicate that navigation and path planning can be brought about with these simple mechanisms. We argue that the graph of local views (snapshots) is a general and biologically plausible means of representing space and integrating the various mechanisms of map behaviour.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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Predicting time series with support vector machines

Müller, K., Smola, A., Rätsch, G., Schölkopf, B., Kohlmorgen, J., Vapnik, V.

In Artificial Neural Networks: ICANN’97, pages: 999-1004, (Editors: Schölkopf, B. , C.J.C. Burges, A.J. Smola), Springer, Berlin, Germany, 7th International Conference on Artificial Neural Networks , October 1997 (inproceedings)

Abstract
Support Vector Machines are used for time series prediction and compared to radial basis function networks. We make use of two different cost functions for Support Vectors: training with (i) an e insensitive loss and (ii) Huber's robust loss function and discuss how to choose the regularization parameters in these models. Two applications are considered: data from (a) a noisy (normal and uniform noise) Mackey Glass equation and (b) the Santa Fe competition (set D). In both cases Support Vector Machines show an excellent performance. In case (b) the Support Vector approach improves the best known result on the benchmark by a factor of 29%.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Masking by plaid patterns is not explained by adaptation, simple contrast gain-control or distortion products

Wichmann, F., Tollin, D.

Investigative Ophthamology and Visual Science, 38 (4), pages: S631, 1997 (poster)

ei

[BibTex]

[BibTex]


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Das Spiel mit dem künstlichen Leben.

Schölkopf, B.

Frankfurter Allgemeine Zeitung, Wissenschaftsbeilage, June 1997 (misc)

ei

[BibTex]

[BibTex]


no image
Predicting time series with support vectur machines

Müller, K., Smola, A., Rätsch, G., Schölkopf, B., Kohlmorgen, J., Vapnik, V.

In Artificial neural networks: ICANN ’97, pages: 999-1004, (Editors: W Gerstner and A Germond and M Hasler and J-D Nicoud), Springer, Berlin, Germany, 7th International Conference on Artificial Neural Networks , October 1997 (inproceedings)

Abstract
Support Vector Machines are used for time series prediction and compared to radial basis function networks. We make use of two different cost functions for Support Vectors: training with (i) an e insensitive loss and (ii) Huber's robust loss function and discuss how to choose the regularization parameters in these models. Two applications are considered: data from (a) a noisy (normal and uniform noise) Mackey Glass equation and (b) the Santa Fe competition (set D). In both cases Support Vector Machines show an excellent performance. In case (b) the Support Vector approach improves the best known result on the benchmark by a factor of 29%.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]