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Robust estimation of multiple surface shapes from occluded textures

Black, M. J., Rosenholtz, R.

In International Symposium on Computer Vision, pages: 485-490, Miami, FL, November 1995 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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View-based cognitive map learning by an autonomous robot

Mallot, H., Bülthoff, H., Georg, P., Schölkopf, B., Yasuhara, K.

In Proceedings International Conference on Artificial Neural Networks, vol. 2, pages: 381-386, (Editors: Fogelman-Soulié, F.), EC2, Paris, France, Conférence Internationale sur les Réseaux de Neurones Artificiels (ICANN '95), October 1995 (inproceedings)

Abstract
This paper presents a view-based approach to map learning and navigation in mazes. By means of graph theory we have shown that the view-graph is a sufficient representation for map behaviour such as path planning. A neural network for unsupervised learning of the view-graph from sequences of views is constructed. We use a modified Kohonen (1988) learning rule that transforms temporal sequence (rather than featural similarity) into connectedness. In the main part of the paper, we present a robot implementation of the scheme. The results show that the proposed network is able to support map behaviour in simple environments.

ei

PDF [BibTex]

PDF [BibTex]


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Extracting support data for a given task

Schölkopf, B., Burges, C., Vapnik, V.

In First International Conference on Knowledge Discovery & Data Mining (KDD-95), pages: 252-257, (Editors: UM Fayyad and R Uthurusamy), AAAI Press, Menlo Park, CA, USA, August 1995 (inproceedings)

Abstract
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vector Algorithm to train three different types of handwritten digit classifiers, we observed that these types of classifiers construct their decision surface from strongly overlapping small (k: 4%) subsets of the data base. This finding opens up the possibiiity of compressing data bases significantly by disposing of the data which is not important for the solution of a given task. In addition, we show that the theory allows us to predict the classifier that will have the best generalization ability, based solely on performance on the training set and characteristics of the learning machines. This finding is important for cases where the amount of available data is limited.

ei

PDF [BibTex]

PDF [BibTex]


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The PLAYBOT Project

Tsotsos, J. K., Dickinson, S., Jenkin, M., Milios, E., Jepson, A., Down, B., Amdur, E., Stevenson, S., Black, M., Metaxas, D., Cooperstock, J., Culhane, S., Nuflo, F., Verghese, G., Wai, W., Wilkes, D., Ye, Y.

In Proc. IJCAI Workshop on AI Applications for Disabled People, Montreal, August 1995 (inproceedings)

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abstract [BibTex]

abstract [BibTex]


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A kendama learning robot based on a dynamic optimization theory

Miyamoto, H., Gandolfo, F., Gomi, H., Schaal, S., Koike, Y., Osu, R., Nakano, E., Kawato, M.

In Preceedings of the 4th IEEE International Workshop on Robot and Human Communication (RO-MAN’95), pages: 327-332, Tokyo, July 1995, clmc (inproceedings)

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[BibTex]

[BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 11.06.54
Recognizing facial expressions under rigid and non-rigid facial motions using local parametric models of image motion

Black, M. J., Yacoob, Y.

In International Workshop on Automatic Face- and Gesture-Recognition, Zurich, July 1995 (inproceedings)

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video abstract [BibTex]

video abstract [BibTex]


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Image segmentation using robust mixture models

Black, M. J., Jepson, A. D.

US Pat. 5,802,203, June 1995 (patent)

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pdf on-line at USPTO [BibTex]

pdf on-line at USPTO [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 11.24.02
Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion

Black, M. J., Yacoob, Y.

In Fifth International Conf. on Computer Vision, ICCV’95, pages: 347-381, Boston, MA, June 1995 (inproceedings)

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 performs with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.

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pdf video publisher site [BibTex]

pdf video publisher site [BibTex]


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A computational model for shape from texture for multiple textures

Black, M. J., Rosenholtz, R.

Investigative Ophthalmology and Visual Science Supplement, Vol. 36, No. 4, pages: 2202, March 1995 (conference)

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abstract [BibTex]

abstract [BibTex]


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View-Based Cognitive Mapping and Path Planning

Schölkopf, B., Mallot, H.

Adaptive Behavior, 3(3):311-348, January 1995 (article)

Abstract
This article presents a scheme for learning a cognitive map of a maze from a sequence of views and movement decisions. The scheme is based on an intermediate representation called the view graph, whose nodes correspond to the views whereas the labeled edges represent the movements leading from one view to another. By means of a graph theoretical reconstruction method, the view graph is shown to carry complete information on the topological and directional structure of the maze. Path planning can be carried out directly in the view graph without actually performing this reconstruction. A neural network is presented that learns the view graph during a random exploration of the maze. It is based on an unsupervised competitive learning rule translating temporal sequence (rather than similarity) of views into connectedness in the network. The network uses its knowledge of the topological and directional structure of the maze to generate expectations about which views are likely to be encountered next, improving the view-recognition performance. Numerical simulations illustrate the network's ability for path planning and the recognition of views degraded by random noise. The results are compared to findings of behavioral neuroscience.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Suppression and creation of chaos in a periodically forced Lorenz system.

Franz, MO., Zhang, MH.

Physical Review, E 52, pages: 3558-3565, 1995 (article)

Abstract
Periodic forcing is introduced into the Lorenz model to study the effects of time-dependent forcing on the behavior of the system. Such a nonautonomous system stays dissipative and has a bounded attracting set which all trajectories finally enter. The possible kinds of attracting sets are restricted to periodic orbits and strange attractors. A large-scale survey of parameter space shows that periodic forcing has mainly three effects in the Lorenz system depending on the forcing frequency: (i) Fixed points are replaced by oscillations around them; (ii) resonant periodic orbits are created both in the stable and the chaotic region; (iii) chaos is created in the stable region near the resonance frequency and in periodic windows. A comparison to other studies shows that part of this behavior has been observed in simulations of higher truncations and real world experiments. Since very small modulations can already have a considerable effect, this suggests that periodic processes such as annual or diurnal cycles should not be omitted even in simple climate models.

ei

[BibTex]

[BibTex]


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A New Method for Constructing Artificial Neural Networks

Vapnik, V., Burges, C., Schölkopf, B.

AT & T Bell Laboratories, 1995 (techreport)

ei

[BibTex]

[BibTex]


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Image segmentation from motion: just the loss of high-spatial-frequency content ?

Wichmann, F., Henning, G.

Perception, 24, pages: S19, 1995 (poster)

Abstract
The human contrast sensitivity function (CSF) is bandpass for stimuli of low temporal frequency but, for moving stimuli, results in a low-pass CSF with large high spatial-frequency losses. Thus the high spatial-frequency content of images moving on the retina cannot be seen; motion perception could be facilitated by, or even be based on, the selective loss of high spatial-frequency content. 2-AFC image segmentation experiments were conducted with segmentation based on motion or on form. In the latter condition, the form difference mirrored that produced by moving stimuli. This was accomplished by generating stimulus elements which were spectrally either broadband or low-pass. For the motion used, the spectral difference between static broadband and static low-pass elements matched the spectral difference between moving and static broadband elements. On the hypothesis that segmentation from motion is based on the detection of regions devoid of high spatial-frequencies, both tasks should be similarly difficult for human observers. However, neither image segmentation (nor, incidentally, motion detection) was sensitive to the high spatial-frequency content of the stimuli. Thus changes in perceptual form produced by moving stimuli appear not to be used as a cue for image segmentation.

ei

[BibTex]


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Visual tracking for moving multiple objects: an integration of vision and control

Sitti, M, Bozma, I, Denker, A

In Industrial Electronics, 1995. ISIE’95., Proceedings of the IEEE International Symposium on, 2, pages: 535-540, 1995 (inproceedings)

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[BibTex]

[BibTex]


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Batting a ball: Dynamics of a rhythmic skill

Sternad, D., Schaal, S., Atkeson, C. G.

In Studies in Perception and Action, pages: 119-122, (Editors: Bardy, B.;Bostma, R.;Guiard, Y.), Erlbaum, Hillsdayle, NJ, 1995, clmc (inbook)

am

[BibTex]

[BibTex]


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Memory-based neural networks for robot learning

Atkeson, C. G., Schaal, S.

Neurocomputing, 9, pages: 1-27, 1995, clmc (article)

Abstract
This paper explores a memory-based approach to robot learning, using memory-based neural networks to learn models of the task to be performed. Steinbuch and Taylor presented neural network designs to explicitly store training data and do nearest neighbor lookup in the early 1960s. In this paper their nearest neighbor network is augmented with a local model network, which fits a local model to a set of nearest neighbors. This network design is equivalent to a statistical approach known as locally weighted regression, in which a local model is formed to answer each query, using a weighted regression in which nearby points (similar experiences) are weighted more than distant points (less relevant experiences). We illustrate this approach by describing how it has been used to enable a robot to learn a difficult juggling task. Keywords: memory-based, robot learning, locally weighted regression, nearest neighbor, local models.

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link (url) [BibTex]

link (url) [BibTex]

1993


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Mixture models for optical flow computation

Jepson, A., Black, M.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-93, pages: 760-761, New York, NY, June 1993 (inproceedings)

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pdf abstract tech report [BibTex]

1993


pdf abstract tech report [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 11.52.45
A framework for the robust estimation of optical flow

(Helmholtz Prize)

Black, M. J., Anandan, P.

In Fourth International Conf. on Computer Vision, ICCV-93, pages: 231-236, Berlin, Germany, May 1993 (inproceedings)

Abstract
Most approaches for estimating optical flow assume that, within a finite image region, only a single motion is present. This single motion assumption is violated in common situations involving transparency, depth discontinuities, independently moving objects, shadows, and specular reflections. To robustly estimate optical flow, the single motion assumption must be relaxed. This work describes a framework based on robust estimation that addresses violations of the brightness constancy and spatial smoothness assumptions caused by multiple motions. We show how the robust estimation framework can be applied to standard formulations of the optical flow problem thus reducing their sensitivity to violations of their underlying assumptions. The approach has been applied to three standard techniques for recovering optical flow: area-based regression, correlation, and regularization with motion discontinuities. This work focuses on the recovery of multiple parametric motion models within a region as well as the recovery of piecewise-smooth flow fields and provides examples with natural and synthetic image sequences.

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pdf video abstract code [BibTex]

pdf video abstract code [BibTex]


Thumb xl bildschirmfoto 2013 01 15 um 11.07.28
Mixture models for optical flow computation

Jepson, A., Black, M.

In Partitioning Data Sets, DIMACS Workshop, pages: 271-286, (Editors: Ingemar Cox, Pierre Hansen, and Bela Julesz), AMS Pub, Providence, RI., April 1993 (incollection)

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pdf [BibTex]

pdf [BibTex]


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Presynaptic and Postsynaptic Competition in models for the Development of Neuromuscular Connections

Rasmussen, CE., Willshaw, DJ.

Biological Cybernetics, 68, pages: 409-419, 1993 (article)

Abstract
The development of the nervous system involves in many cases interactions on a local scale rather than the execution of a fully specified genetic blueprint. The problem is to discover the nature of these interactions and the factors on which they depend. The withdrawal of polyinnervation in developing muscle is an example where such competitive interactions play an important role. We examine the possible types of competition in formal models that have plausible biological implementations. By relating the behaviour of the models to the anatomical and physiological findings we show that a model that incorporates two types of competition is superior to others. Analysis suggests that the phenomenon of intrinsic withdrawal is a side effect of the competitive mechanisms rather than a separate non-competitive feature. Full scale computer simulations have been used to confirm the capabilities of this model.

ei

PostScript [BibTex]

PostScript [BibTex]


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Cartesian Dynamics of Simple Molecules: X Linear Quadratomics (C∞v Symmetry).

Anderson, A., Davison, T., Nagi, N., Schlueter, S.

Spectroscopy Letters, 26, pages: 509-522, 1993 (article)

ei

[BibTex]

[BibTex]


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Learning passive motor control strategies with genetic algorithms

Schaal, S., Sternad, D.

In 1992 Lectures in complex systems, pages: 913-918, (Editors: Nadel, L.;Stein, D.), Addison-Wesley, Redwood City, CA, 1993, clmc (inbook)

Abstract
This study investigates learning passive motor control strategies. Passive control is understood as control without active error correction; the movement is stabilized by particular properties of the controlling dynamics. We analyze the task of juggling a ball on a racket. An approximation to the optimal solution of the task is derived by means of optimization theory. In order to model the learning process, the problem is coded for a genetic algorithm in representations without sensory or with sensory information. For all representations the genetic algorithm is able to find passive control strategies, but learning speed and the quality of the outcome are significantly different. A comparison with data from human subjects shows that humans seem to apply yet different movement strategies to the ones proposed. For the feedback representation some implications arise for learning from demonstration.

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link (url) [BibTex]

link (url) [BibTex]


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A genetic algorithm for evolution from an ecological perspective

Sternad, D., Schaal, S.

In 1992 Lectures in Complex Systems, pages: 223-231, (Editors: Nadel, L.;Stein, D.), Addison-Wesley, Redwood City, CA, 1993, clmc (inbook)

Abstract
In the population model presented, an evolutionary dynamic is explored which is based on the operator characteristics of genetic algorithms. An essential modification in the genetic algorithms is the inclusion of a constraint in the mixing of the gene pool. The pairing for the crossover is governed by a selection principle based on a complementarity criterion derived from the theoretical tenet of perception-action (P-A) mutuality of ecological psychology. According to Swenson and Turvey [37] P-A mutuality underlies evolution and is an integral part of its thermodynamics. The present simulation tested the contribution of P-A-cycles in evolutionary dynamics. A numerical experiment compares the population's evolution with and without this intentional component. The effect is measured in the difference of the rate of energy dissipation, as well as in three operationalized aspects of complexity. The results support the predicted increase in the rate of energy dissipation, paralleled by an increase in the average heterogeneity of the population. Furthermore, the spatio-temporal evolution of the system is tested for the characteristic power-law relations of a nonlinear system poised in a critical state. The frequency distribution of consecutive increases in population size shows a significantly different exponent in functional relationship.

am

[BibTex]

[BibTex]


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Roles for memory-based learning in robotics

Atkeson, C. G., Schaal, S.

In Proceedings of the Sixth International Symposium on Robotics Research, pages: 503-521, Hidden Valley, PA, 1993, clmc (inproceedings)

am

[BibTex]

[BibTex]


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Design concurrent calculation: A CAD- and data-integrated approach

Schaal, S., Ehrlenspiel, K.

Journal of Engineering Design, 4, pages: 71-85, 1993, clmc (article)

Abstract
Besides functional regards, product design demands increasingly more for further reaching considerations. Quality alone cannot suffice anymore to compete in the market; design for manufacturability, for assembly, for recycling, etc., are well-known keywords. Those can largely be reduced to the necessity of design for costs. This paper focuses on a CAD-based approach to design concurrent calculation. It will discuss how, in the meantime well-established, tools like feature technology, knowledge-based systems, and relational databases can be blended into one coherent concept to achieve an entirely CAD- and data-integrated cost information tool. This system is able to extract data from the CAD-system, combine it with data about the company specific manufacturing environment, and subsequently autonomously evaluate manufacturability aspects and costs of the given CAD-model. Within minutes the designer gets quantitative in-formation about the major cost sources of his/her design. Additionally, some alternative methods for approximating manu-facturing times from empirical data, namely neural networks and local weighted regression, are introduced.

am

[BibTex]

[BibTex]


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Action, representation, and purpose: Re-evaluating the foundations of computational vision

Black, M. J., Aloimonos, Y., Brown, C. M., Horswill, I., Malik, J., G. Sandini, , Tarr, M. J.

In International Joint Conference on Artificial Intelligence, IJCAI-93, pages: 1661-1666, Chambery, France, 1993 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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Open loop stable control strategies for robot juggling

Schaal, S., Atkeson, C. G.

In IEEE International Conference on Robotics and Automation, 3, pages: 913-918, Piscataway, NJ: IEEE, Georgia, Atlanta, May 2-6, 1993, clmc (inproceedings)

Abstract
In a series of case studies out of the field of dynamic manipulation (Mason, 1992), different principles for open loop stable control are introduced and analyzed. This investigation may provide some insight into how open loop control can serve as a useful foundation for closed loop control and, particularly, what to focus on in learning control. 

am

link (url) [BibTex]

link (url) [BibTex]

1991


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Dynamic motion estimation and feature extraction over long image sequences

Black, M. J., Anandan, P.

In Proc. IJCAI Workshop on Dynamic Scene Understanding, Sydney, Australia, August 1991 (inproceedings)

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[BibTex]

1991


[BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 12.06.42
Robust dynamic motion estimation over time

(IEEE Computer Society Outstanding Paper Award)

Black, M. J., Anandan, P.

In Proc. Computer Vision and Pattern Recognition, CVPR-91,, pages: 296-302, Maui, Hawaii, June 1991 (inproceedings)

Abstract
This paper presents a novel approach to incrementally estimating visual motion over a sequence of images. We start by formulating constraints on image motion to account for the possibility of multiple motions. This is achieved by exploiting the notions of weak continuity and robust statistics in the formulation of the minimization problem. The resulting objective function is non-convex. Traditional stochastic relaxation techniques for minimizing such functions prove inappropriate for the task. We present a highly parallel incremental stochastic minimization algorithm which has a number of advantages over previous approaches. The incremental nature of the scheme makes it truly dynamic and permits the detection of occlusion and disocclusion boundaries.

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pdf video abstract [BibTex]

pdf video abstract [BibTex]


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Ways to smarter CAD-systems

Ehrlenspiel, K., Schaal, S.

In Proceedings of ICED’91Heurista, pages: 10-16, (Editors: Hubka), Edition, Schriftenreihe WDK 21. Zürich, 1991, clmc (inbook)

am

[BibTex]

[BibTex]