Publications | Empirical Inference - Max Planck Institute for Intelligent Systems

44 results (View BibTeX file of all listed publications)

2015

Diversity of sharp wave-ripples in the CA1 of the macaque hippocampus and their brain wide signatures

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), October 2015 (poster)

2015

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M. Diversity of sharp wave-ripples in the CA1 of the macaque hippocampus and their brain wide signatures 45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), October 2015 (poster)

link (url) [BibTex]

Retrospective rigid motion correction of undersampled MRI data

Loktyushin, A., Babayeva, M., Gallichan, D., Krueger, G., Scheffler, K., Kober, T.

23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, ISMRM, June 2015 (poster)

[BibTex]

Loktyushin, A., Babayeva, M., Gallichan, D., Krueger, G., Scheffler, K., Kober, T. Retrospective rigid motion correction of undersampled MRI data 23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, ISMRM, June 2015 (poster)

[BibTex]

Improving Quantitative Susceptibility and R2* Mapping by Applying Retrospective Motion Correction

Feng, X., Loktyushin, A., Deistung, A., Reichenbach, J. R.

23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, ISMRM, June 2015 (poster)

[BibTex]

Feng, X., Loktyushin, A., Deistung, A., Reichenbach, J. R. Improving Quantitative Susceptibility and R2* Mapping by Applying Retrospective Motion Correction 23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, ISMRM, June 2015 (poster)

[BibTex]

Increasing the sensitivity of Kepler to Earth-like exoplanets

Foreman-Mackey, D., Hogg, D., Schölkopf, B., Wang, D.

Workshop: 225th American Astronomical Society Meeting 2015 , pages: 105.01D, 2015 (poster)

Web link (url) [BibTex]

Foreman-Mackey, D., Hogg, D., Schölkopf, B., Wang, D. Increasing the sensitivity of Kepler to Earth-like exoplanets Workshop: 225th American Astronomical Society Meeting 2015 , pages: 105.01D, 2015 (poster)

Web link (url) [BibTex]

Calibrating the pixel-level Kepler imaging data with a causal data-driven model

Wang, D., Foreman-Mackey, D., Hogg, D., Schölkopf, B.

Workshop: 225th American Astronomical Society Meeting 2015 , pages: 258.08, 2015 (poster)

Web link (url) [BibTex]

Wang, D., Foreman-Mackey, D., Hogg, D., Schölkopf, B. Calibrating the pixel-level Kepler imaging data with a causal data-driven model Workshop: 225th American Astronomical Society Meeting 2015 , pages: 258.08, 2015 (poster)

Web link (url) [BibTex]

Assessment of tumor heterogeneity using unsupervised graph based clustering of multi-modality imaging data

Katiyar, P., Divine, M. R., Pichler, B. J., Disselhorst, J. A.

European Molecular Imaging Meeting, 2015 (poster)

[BibTex]

Katiyar, P., Divine, M. R., Pichler, B. J., Disselhorst, J. A. Assessment of tumor heterogeneity using unsupervised graph based clustering of multi-modality imaging data European Molecular Imaging Meeting, 2015 (poster)

[BibTex]

Novel segmentation of dynamic [18]F-FDG PET bypasses the need of arterial plasma input function, delivering a robust quantification of the tumor microenvironment

Katiyar, P., Divine, M. R., Pichler, B. J., Disselhorst, J. A.

World Molecular Imaging Conference, 2015 (poster)

[BibTex]

Katiyar, P., Divine, M. R., Pichler, B. J., Disselhorst, J. A. Novel segmentation of dynamic [18]F-FDG PET bypasses the need of arterial plasma input function, delivering a robust quantification of the tumor microenvironment World Molecular Imaging Conference, 2015 (poster)

[BibTex]

Disparity estimation from a generative light field model

Köhler, R., Schölkopf, B., Hirsch, M.

IEEE International Conference on Computer Vision (ICCV 2015), Workshop on Inverse Rendering, 2015, Note: This work has been presented as a poster and is not included in the workshop proceedings. (poster)

[BibTex]

Köhler, R., Schölkopf, B., Hirsch, M. Disparity estimation from a generative light field model IEEE International Conference on Computer Vision (ICCV 2015), Workshop on Inverse Rendering, 2015, Note: This work has been presented as a poster and is not included in the workshop proceedings. (poster)

[BibTex]

2008

Variational Bayesian Model Selection in Linear Gaussian State-Space based Models

Chiappa, S.

International Workshop on Flexible Modelling: Smoothing and Robustness (FMSR 2008), 2008, pages: 1, November 2008 (poster)

Web [BibTex]

2008

Chiappa, S. Variational Bayesian Model Selection in Linear Gaussian State-Space based Models International Workshop on Flexible Modelling: Smoothing and Robustness (FMSR 2008), 2008, pages: 1, November 2008 (poster)

Web [BibTex]

Towards the neural basis of the flash-lag effect

Ecker, A., Berens, P., Hoenselaar, A., Subramaniyan, M., Tolias, A., Bethge, M.

International Workshop on Aspects of Adaptive Cortex Dynamics, 2008, pages: 1, September 2008 (poster)

PDF [BibTex]

Ecker, A., Berens, P., Hoenselaar, A., Subramaniyan, M., Tolias, A., Bethge, M. Towards the neural basis of the flash-lag effect International Workshop on Aspects of Adaptive Cortex Dynamics, 2008, pages: 1, September 2008 (poster)

PDF [BibTex]

Policy Learning: A Unified Perspective With Applications In Robotics

Peters, J., Kober, J., Nguyen-Tuong, D.

8th European Workshop on Reinforcement Learning for Robotics (EWRL 2008), 8, pages: 10, July 2008 (poster)

Abstract

Policy Learning approaches are among the best suited methods for high-dimensional, continuous control systems such as anthropomorphic robot arms and humanoid robots. In this paper, we show two contributions: firstly, we show a unified perspective which allows us to derive several policy learning al- gorithms from a common point of view, i.e, policy gradient algorithms, natural- gradient algorithms and EM-like policy learning. Secondly, we present several applications to both robot motor primitive learning as well as to robot control in task space. Results both from simulation and several different real robots are shown.

PDF [BibTex]

Peters, J., Kober, J., Nguyen-Tuong, D. Policy Learning: A Unified Perspective With Applications In Robotics 8th European Workshop on Reinforcement Learning for Robotics (EWRL 2008), 8, pages: 10, July 2008 (poster)

PDF [BibTex]

Reinforcement Learning of Perceptual Coupling for Motor Primitives

Kober, J., Peters, J.

8th European Workshop on Reinforcement Learning for Robotics (EWRL 2008), 8, pages: 16, July 2008 (poster)

Abstract

Reinforcement learning is a natural choice for the learning of complex motor tasks by reward-related self-improvement. As the space of movements is high-dimensional and continuous, a policy parametrization is needed which can be used in this context. Traditional motor primitive approaches deal largely with open-loop policies which can only deal with small perturbations. In this paper, we present a new type of motor primitive policies which serve as closed-loop policies together with an appropriate learning algorithm. Our new motor primitives are an augmented version version of the dynamic systems motor primitives that incorporates perceptual coupling to external variables. We show that these motor primitives can perform complex tasks such a Ball-in-a-Cup or Kendama task even with large variances in the initial conditions where a human would hardly be able to learn this task. We initialize the open-loop policies by imitation learning and the perceptual coupling with a handcrafted solution. We first improve the open-loop policies and subsequently the perceptual coupling using a novel reinforcement learning method which is particularly well-suited for motor primitives.

PDF [BibTex]

Kober, J., Peters, J. Reinforcement Learning of Perceptual Coupling for Motor Primitives 8th European Workshop on Reinforcement Learning for Robotics (EWRL 2008), 8, pages: 16, July 2008 (poster)

PDF [BibTex]

Flexible Models for Population Spike Trains

Bethge, M., Macke, J., Berens, P., Ecker, A., Tolias, A.

AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles, 2, pages: 52, June 2008 (poster)

PDF [BibTex]

Bethge, M., Macke, J., Berens, P., Ecker, A., Tolias, A. Flexible Models for Population Spike Trains AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles, 2, pages: 52, June 2008 (poster)

PDF [BibTex]

Pairwise Correlations and Multineuronal Firing Patterns in the Primary Visual Cortex of the Awake, Behaving Macaque

Berens, P., Ecker, A., Subramaniyan, M., Macke, J., Hauck, P., Bethge, M., Tolias, A.

AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles, 2, pages: 48, June 2008 (poster)

PDF [BibTex]

Berens, P., Ecker, A., Subramaniyan, M., Macke, J., Hauck, P., Bethge, M., Tolias, A. Pairwise Correlations and Multineuronal Firing Patterns in the Primary Visual Cortex of the Awake, Behaving Macaque AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles, 2, pages: 48, June 2008 (poster)

PDF [BibTex]

Visual saliency re-visited: Center-surround patterns emerge as optimal predictors for human fixation targets

Wichmann, F., Kienzle, W., Schölkopf, B., Franz, M.

Journal of Vision, 8(6):635, 8th Annual Meeting of the Vision Sciences Society (VSS), June 2008 (poster)

Abstract

Humans perceives the world by directing the center of gaze from one location to another via rapid eye movements, called saccades. In the period between saccades the direction of gaze is held fixed for a few hundred milliseconds (fixations). It is primarily during fixations that information enters the visual system. Remarkably, however, after only a few fixations we perceive a coherent, high-resolution scene despite the visual acuity of the eye quickly decreasing away from the center of gaze: This suggests an effective strategy for selecting saccade targets. Top-down effects, such as the observer's task, thoughts, or intentions have an effect on saccadic selection. Equally well known is that bottom-up effects-local image structure-influence saccade targeting regardless of top-down effects. However, the question of what the most salient visual features are is still under debate. Here we model the relationship between spatial intensity patterns in natural images and the response of the saccadic system using tools from machine learning. This allows us to identify the most salient image patterns that guide the bottom-up component of the saccadic selection system, which we refer to as perceptive fields. We show that center-surround patterns emerge as the optimal solution to the problem of predicting saccade targets. Using a novel nonlinear system identification technique we reduce our learned classifier to a one-layer feed-forward network which is surprisingly simple compared to previously suggested models assuming more complex computations such as multi-scale processing, oriented filters and lateral inhibition. Nevertheless, our model is equally predictive and generalizes better to novel image sets. Furthermore, our findings are consistent with neurophysiological hardware in the superior colliculus. Bottom-up visual saliency may thus not be computed cortically as has been thought previously.

Web DOI [BibTex]

Wichmann, F., Kienzle, W., Schölkopf, B., Franz, M. Visual saliency re-visited: Center-surround patterns emerge as optimal predictors for human fixation targets Journal of Vision, 8(6):635, 8th Annual Meeting of the Vision Sciences Society (VSS), June 2008 (poster)

Web DOI [BibTex]

Analysis of Pattern Recognition Methods in Classifying Bold Signals in Monkeys at 7-Tesla

Ku, S., Gretton, A., Macke, J., Tolias, A., Logothetis, N.

AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles, 2, pages: 67, June 2008 (poster)

Abstract

Pattern recognition methods have shown that fMRI data can reveal significant information about brain activity. For example, in the debate of how object-categories are represented in the brain, multivariate analysis has been used to provide evidence of distributed encoding schemes. Many follow-up studies have employed different methods to analyze human fMRI data with varying degrees of success. In this study we compare four popular pattern recognition methods: correlation analysis, support-vector machines (SVM), linear discriminant analysis and Gaussian naïve Bayes (GNB), using data collected at high field (7T) with higher resolution than usual fMRI studies. We investigate prediction performance on single trials and for averages across varying numbers of stimulus presentations. The performance of the various algorithms depends on the nature of the brain activity being categorized: for several tasks, many of the methods work well, whereas for others, no methods perform above chance level. An important factor in overall classification performance is careful preprocessing of the data, including dimensionality reduction, voxel selection, and outlier elimination.

[BibTex]

Ku, S., Gretton, A., Macke, J., Tolias, A., Logothetis, N. Analysis of Pattern Recognition Methods in Classifying Bold Signals in Monkeys at 7-Tesla AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles, 2, pages: 67, June 2008 (poster)

[BibTex]

The role of stimulus correlations for population decoding in the retina

Schwartz, G., Macke, J., Berry, M.

Computational and Systems Neuroscience 2008 (COSYNE 2008), 5, pages: 172, March 2008 (poster)

PDF Web [BibTex]

Schwartz, G., Macke, J., Berry, M. The role of stimulus correlations for population decoding in the retina Computational and Systems Neuroscience 2008 (COSYNE 2008), 5, pages: 172, March 2008 (poster)

PDF Web [BibTex]

2004

S-cones contribute to flicker brightness in human vision

Wehrhahn, C., Hill, NJ., Dillenburger, B.

34(174.12), 34th Annual Meeting of the Society for Neuroscience (Neuroscience), October 2004 (poster)

Abstract

In the retina of primates three cone types sensitive to short, middle and long wavelengths of light convert photons into electrical signals. Many investigators have presented evidence that, in color normal observers, the signals of cones sensitive to short wavelengths of light (S-cones) do not contribute to the perception of brightness of a colored surface when this is alternated with an achromatic reference (flicker brightness). Other studies indicate that humans do use S-cone signals when performing this task. Common to all these studies is the small number of observers, whose performance data are reported. Considerable variability in the occurrence of cone types across observers has been found, but, to our knowledge, no cone counts exist from larger populations of humans. We reinvestigated how much the S-cones contribute to flicker brightness. 76 color normal observers were tested in a simple psychophysical procedure neutral to the cone type occurence (Teufel & Wehrhahn (2000), JOSA A 17: 994 - 1006). The data show that, in the majority of our observers, S-cones provide input with a negative sign - relative to L- and M-cone contribution - in the task in question. There is indeed considerable between-subject variability such that for 20 out of 76 observers the magnitude of this input does not differ significantly from 0. Finally, we argue that the sign of S-cone contribution to flicker brightness perception by an observer cannot be used to infer the relative sign their contributions to the neuronal signals carrying the information leading to the perception of flicker brightness. We conclude that studies which use only a small number of observers may easily fail to find significant evidence for the small but significant population tendency for the S-cones to contribute to flicker brightness. Our results confirm all earlier results and reconcile their contradictory interpretations.

Web [BibTex]

2004

Wehrhahn, C., Hill, NJ., Dillenburger, B. S-cones contribute to flicker brightness in human vision 34(174.12), 34th Annual Meeting of the Society for Neuroscience (Neuroscience), October 2004 (poster)

Web [BibTex]

Learning Motor Primitives with Reinforcement Learning

Peters, J., Schaal, S.

AAAI Fall Symposium on Real-Life Reinforcement Learning 2004, 2004, pages: 1, October 2004 (poster)

Web [BibTex]

Peters, J., Schaal, S. Learning Motor Primitives with Reinforcement Learning AAAI Fall Symposium on Real-Life Reinforcement Learning 2004, 2004, pages: 1, October 2004 (poster)

Web [BibTex]

Learning Motor Primitives with Reinforcement Learning

Peters, J., Schaal, S.

11th Joint Symposium on Neural Computation (JSNC 2004), 11, pages: 1, May 2004 (poster)

Abstract

One of the major challenges in action generation for robotics and in the understanding of human motor control is to learn the "building blocks of move- ment generation," or more precisely, motor primitives. Recently, Ijspeert et al. [1, 2] suggested a novel framework how to use nonlinear dynamical systems as motor primitives. While a lot of progress has been made in teaching these mo- tor primitives using supervised or imitation learning, the self-improvement by interaction of the system with the environment remains a challenging problem. In this poster, we evaluate different reinforcement learning approaches can be used in order to improve the performance of motor primitives. For pursuing this goal, we highlight the difficulties with current reinforcement learning methods, and line out how these lead to a novel algorithm which is based on natural policy gradients [3]. We compare this algorithm to previous reinforcement learning algorithms in the context of dynamic motor primitive learning, and show that it outperforms these by at least an order of magnitude. We demonstrate the efficiency of the resulting reinforcement learning method for creating complex behaviors for automous robotics. The studied behaviors will include both discrete, finite tasks such as baseball swings, as well as complex rhythmic patterns as they occur in biped locomotion.

Web [BibTex]

Peters, J., Schaal, S. Learning Motor Primitives with Reinforcement Learning 11th Joint Symposium on Neural Computation (JSNC 2004), 11, pages: 1, May 2004 (poster)

Web [BibTex]

Human Classification Behaviour Revisited by Machine Learning

Graf, A., Wichmann, F., Bülthoff, H., Schölkopf, B.

7, pages: 134, (Editors: Bülthoff, H.H., H.A. Mallot, R. Ulrich and F.A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), Febuary 2004 (poster)

Abstract

We attempt to understand visual classication in humans using both psychophysical and machine learning techniques. Frontal views of human faces were used for a gender classication task. Human subjects classied the faces and their gender judgment, reaction time (RT) and condence rating (CR) were recorded for each face. RTs are longer for incorrect answers than for correct ones, high CRs are correlated with low classication errors and RTs decrease as the CRs increase. This results suggest that patterns difcult to classify need more computation by the brain than patterns easy to classify. Hyperplane learning algorithms such as Support Vector Machines (SVM), Relevance Vector Machines (RVM), Prototype learners (Prot) and K-means learners (Kmean) were used on the same classication task using the Principal Components of the texture and oweld representation of the faces. The classication performance of the learning algorithms was estimated using the face database with the true gender of the faces as labels, and also with the gender estimated by the subjects. Kmean yield a classication performance close to humans while SVM and RVM are much better. This surprising behaviour may be due to the fact that humans are trained on real faces during their lifetime while they were here tested on articial ones, while the algorithms were trained and tested on the same set of stimuli. We then correlated the human responses to the distance of the stimuli to the separating hyperplane (SH) of the learning algorithms. On the whole stimuli far from the SH are classied more accurately, faster and with higher condence than those near to the SH if we pool data across all our subjects and stimuli. We also nd three noteworthy results. First, SVMs and RVMs can learn to classify faces using the subjects' labels but perform much better when using the true labels. Second, correlating the average response of humans (classication error, RT or CR) with the distance to the SH on a face-by-face basis using Spearman's rank correlation coefcients shows that RVMs recreate human performance most closely in every respect. Third, the mean-of-class prototype, its popularity in neuroscience notwithstanding, is the least human-like classier in all cases examined.

Web [BibTex]

Graf, A., Wichmann, F., Bülthoff, H., Schölkopf, B. Human Classification Behaviour Revisited by Machine Learning 7, pages: 134, (Editors: Bülthoff, H.H., H.A. Mallot, R. Ulrich and F.A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), Febuary 2004 (poster)

Web [BibTex]

m-Alternative-Forced-Choice: Improving the Efficiency of the Method of Constant Stimuli

Jäkel, F., Hill, J., Wichmann, F.

7, pages: 118, 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

We explored several ways to improve the efficiency of measuring psychometric functions without resorting to adaptive procedures. a) The number m of alternatives in an m-alternative-forced-choice (m-AFC) task improves the efficiency of the method of constant stimuli. b) When alternatives are presented simultaneously on different positions on a screen rather than sequentially time can be saved and memory load for the subject can be reduced. c) A touch-screen can further help to make the experimental procedure more intuitive. We tested these ideas in the measurement of contrast sensitivity and compared them to results obtained by sequential presentation in two-interval-forced-choice (2-IFC). Qualitatively all methods (m-AFC and 2-IFC) recovered the characterictic shape of the contrast sensitivity function in three subjects. The m-AFC paradigm only took about 60% of the time of the 2-IFC task. We tried m=2,4,8 and found 4-AFC to give the best model fits and 2-AFC to have the least bias.

Web [BibTex]

Jäkel, F., Hill, J., Wichmann, F. m-Alternative-Forced-Choice: Improving the Efficiency of the Method of Constant Stimuli 7, pages: 118, 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Web [BibTex]

Efficient Approximations for Support Vector Classifiers

Kienzle, W., Franz, M.

7, pages: 68, 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

In face detection, support vector machines (SVM) and neural networks (NN) have been shown to outperform most other classication methods. While both approaches are learning-based, there are distinct advantages and drawbacks to each method: NNs are difcult to design and train but can lead to very small and efcient classiers. In comparison, SVM model selection and training is rather straightforward, and, more importantly, guaranteed to converge to a globally optimal (in the sense of training errors) solution. Unfortunately, SVM classiers tend to have large representations which are inappropriate for time-critical image processing applications. In this work, we examine various existing and new methods for simplifying support vector decision rules. Our goal is to obtain efcient classiers (as with NNs) while keeping the numerical and statistical advantages of SVMs. For a given SVM solution, we compute a cascade of approximations with increasing complexities. Each classier is tuned so that the detection rate is near 100%. At run-time, the rst (simplest) detector is evaluated on the whole image. Then, any subsequent classier is applied only to those positions that have been classied as positive throughout all previous stages. The false positive rate at the end equals that of the last (i.e. most complex) detector. In contrast, since many image positions are discarded by lower-complexity classiers, the average computation time per patch decreases signicantly compared to the time needed for evaluating the highest-complexity classier alone.

Web [BibTex]

Kienzle, W., Franz, M. Efficient Approximations for Support Vector Classifiers 7, pages: 68, 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Web [BibTex]

Selective Attention to Auditory Stimuli: A Brain-Computer Interface Paradigm

Hill, N., Lal, T., Schröder, M., Hinterberger, T., Birbaumer, N., Schölkopf, B.

7, pages: 102, (Editors: Bülthoff, H.H., H.A. Mallot, R. Ulrich and F.A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

During the last 20 years several paradigms for Brain Computer Interfaces have been proposed see [1] for a recent review. They can be divided into (a) stimulus-driven paradigms, using e.g. event-related potentials or visual evoked potentials from an EEG signal, and (b) patient-driven paradigms such as those that use premotor potentials correlated with imagined action, or slow cortical potentials (e.g. [2]). Our aim is to develop a stimulus-driven paradigm that is applicable in practice to patients. Due to the unreliability of visual perception in locked-in patients in the later stages of disorders such as Amyotrophic Lateral Sclerosis, we concentrate on the auditory modality. Speci- cally, we look for the effects, in the EEG signal, of selective attention to one of two concurrent auditory stimulus streams, exploiting the increased activation to attended stimuli that is seen under some circumstances [3]. We present the results of our preliminary experiments on normal subjects. On each of 400 trials, two repetitive stimuli (sequences of drum-beats or other pulsed stimuli) could be heard simultaneously. The two stimuli were distinguishable from one another by their acoustic properties, by their source location (one from a speaker to the left of the subject, the other from the right), and by their differing periodicities. A visual cue preceded the stimulus by 500 msec, indicating which of the two stimuli to attend to, and the subject was instructed to count the beats in the attended stimulus stream. There were up to 6 beats of each stimulus: with equal probability on each trial, all 6 were played, or the fourth was omitted, or the fth was omitted. The 40-channel EEG signals were analyzed ofine to reconstruct which of the streams was attended on each trial. A linear Support Vector Machine [4] was trained on a random subset of the data and tested on the remainder. Results are compared from two types of pre-processing of the signal: for each stimulus stream, (a) EEG signals at the stream's beat periodicity are emphasized, or (b) EEG signals following beats are contrasted with those following missing beats. Both forms of pre-processing show promising results, i.e. that selective attention to one or the other auditory stream yields signals that are classiable signicantly above chance performance. In particular, the second pre-processing was found to be robust to reduction in the number of features used for classication (cf. [5]), helping us to eliminate noise.

PDF Web [BibTex]

Hill, N., Lal, T., Schröder, M., Hinterberger, T., Birbaumer, N., Schölkopf, B. Selective Attention to Auditory Stimuli: A Brain-Computer Interface Paradigm 7, pages: 102, (Editors: Bülthoff, H.H., H.A. Mallot, R. Ulrich and F.A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

PDF Web [BibTex]

Texture and Haptic Cues in Slant Discrimination: Measuring the Effect of Texture Type

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

7, pages: 165, (Editors: Bülthoff, H. H., H. A. Mallot, R. Ulrich, F. A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

In a number of models of depth cue combination the depth percept is constructed via a weighted average combination of independent depth estimations. The inuence of each cue in such average depends on the reliability of the source of information [1,5]. In particular, Ernst and Banks (2002) formulate such combination as that of the minimum variance unbiased estimator that can be constructed from the available cues. We have observed systematic differences in slant discrimination performance of human observers when different types of textures were used as cue to slant [4]. If the depth percept behaves as described above, our measurements of the slopes of the psychometric functions provide the predicted weights for the texture cue for the ranked texture types. However, the results for slant discrimination obtained when combining these texture types with object motion results are difcult to reconcile with the minimum variance unbiased estimator model [3]. This apparent failure of such model might be explained by the existence of a coupling of texture and motion, violating the assumption of independence of cues. Hillis, Ernst, Banks, and Landy (2002) [2] have shown that while for between-modality combination the human visual system has access to the single-cue information, for withinmodality combination (visual cues) the single-cue information is lost. This suggests a coupling between visual cues and independence between visual and haptic cues. Then, in the present study we combined the different texture types with haptic information in a slant discrimination task, to test whether in the between-modality condition these cues are combined as predicted by an unbiased, minimum variance estimator model. The measured weights for the cues were consistent with a combination rule sensitive to the reliability of the sources of information, but did not match the predictions of a statistically optimal combination.

PDF Web [BibTex]

Rosas, P., Wichmann, F., Ernst, M., Wagemans, J. Texture and Haptic Cues in Slant Discrimination: Measuring the Effect of Texture Type 7, pages: 165, (Editors: Bülthoff, H. H., H. A. Mallot, R. Ulrich, F. A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

PDF Web [BibTex]

Efficient Approximations for Support Vector Classiers

Kienzle, W., Franz, M.

7, pages: 68, 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

Web [BibTex]

Kienzle, W., Franz, M. Efficient Approximations for Support Vector Classiers 7, pages: 68, 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Web [BibTex]

EEG Channel Selection for Brain Computer Interface Systems Based on Support Vector Methods

Schröder, M., Lal, T., Bogdan, M., Schölkopf, B.

7, pages: 50, (Editors: Bülthoff, H.H., H.A. Mallot, R. Ulrich and F.A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

A Brain Computer Interface (BCI) system allows the direct interpretation of brain activity patterns (e.g. EEG signals) by a computer. Typical BCI applications comprise spelling aids or environmental control systems supporting paralyzed patients that have lost motor control completely. The design of an EEG based BCI system requires good answers for the problem of selecting useful features during the performance of a mental task as well as for the problem of classifying these features. For the special case of choosing appropriate EEG channels from several available channels, we propose the application of variants of the Support Vector Machine (SVM) for both problems. Although these algorithms do not rely on prior knowledge they can provide more accurate solutions than standard lter methods [1] for feature selection which usually incorporate prior knowledge about neural activity patterns during the performed mental tasks. For judging the importance of features we introduce a new relevance measure and apply it to EEG channels. Although we base the relevance measure for this purpose on the previously introduced algorithms, it does in general not depend on specic algorithms but can be derived using arbitrary combinations of feature selectors and classifiers.

Web [BibTex]

Schröder, M., Lal, T., Bogdan, M., Schölkopf, B. EEG Channel Selection for Brain Computer Interface Systems Based on Support Vector Methods 7, pages: 50, (Editors: Bülthoff, H.H., H.A. Mallot, R. Ulrich and F.A. Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Web [BibTex]

Learning Depth

Sinz, F., Franz, MO.

pages: 69, (Editors: H.H.Bülthoff, H.A.Mallot, R.Ulrich,F.A.Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

Abstract

The depth of a point in space can be estimated by observing its image position from two different viewpoints. The classical approach to stereo vision calculates depth from the two projection equations which together form a stereocamera model. An unavoidable preparatory work for this solution is a calibration procedure, i.e., estimating the external (position and orientation) and internal (focal length, lens distortions etc.) parameters of each camera from a set of points with known spatial position and their corresponding image positions. This is normally done by iteratively linearizing the single camera models and reestimating their parameters according to the error on the known datapoints. The advantage of the classical method is the maximal usage of prior knowledge about the underlying physical processes and the explicit estimation of meaningful model parameters such as focal length or camera position in space. However, the approach neglects the nonlinear nature of the problem such that the results critically depend on the choice of the initial values for the parameters. In this study, we approach the depth estimation problem from a different point of view by applying generic machine learning algorithms to learn the mapping from image coordinates to spatial position. These algorithms do not require any domain knowledge and are able to learn nonlinear functions by mapping the inputs into a higher-dimensional space. Compared to classical calibration, machine learning methods give a direct solution to the depth estimation problem which means that the values of the stereocamera parameters cannot be extracted from the learned mapping. On the poster, we compare the performance of classical camera calibration to that of different machine learning algorithms such as kernel ridge regression, gaussian processes and support vector regression. Our results indicate that generic learning approaches can lead to higher depth accuracies than classical calibration although no domain knowledge is used.

PDF Web [BibTex]

Sinz, F., Franz, MO. Learning Depth pages: 69, (Editors: H.H.Bülthoff, H.A.Mallot, R.Ulrich,F.A.Wichmann), 7th T{\"u}bingen Perception Conference (TWK), February 2004 (poster)

PDF Web [BibTex]

Neural mechanisms underlying control of a Brain-Computer-Interface (BCI): Simultaneous recording of bold-response and EEG

Hinterberger, T., Wilhelm, B., Veit, R., Weiskopf, N., Lal, TN., Birbaumer, N.

2004 (poster)

Abstract

Brain computer interfaces (BCI) enable humans or animals to communicate or activate external devices without muscle activity using electric brain signals. The BCI Thought Translation Device (TTD) uses learned regulation of slow cortical potentials (SCPs), a skill most people and paralyzed patients can acquire with training periods of several hours up to months. The neurophysiological mechanisms and anatomical sources of SCPs and other event-related brain macro-potentials are well understood, but the neural mechanisms underlying learning of the self-regulation skill for BCI-use are unknown. To uncover the relevant areas of brain activation during regulation of SCPs, the TTD was combined with functional MRI and EEG was recorded inside the MRI scanner in twelve healthy participants who have learned to regulate their SCP with feedback and reinforcement. The results demonstrate activation of specific brain areas during execution of the brain regulation skill: successf! ul control of cortical positivity allowing a person to activate an external device was closely related to an increase of BOLD (blood oxygen level dependent) response in the basal ganglia and frontal premotor deactivation indicating learned regulation of a cortical-striatal loop responsible for local excitation thresholds of cortical assemblies. The data suggest that human users of a BCI learn the regulation of cortical excitation thresholds of large neuronal assemblies as a prerequisite of direct brain communication: the learning of this skill depends critically on an intact and flexible interaction between these cortico-basal ganglia-circuits. Supported by the Deutsche Forschungsgemeinschaft (DFG) and the National Institute of Health (NIH).

[BibTex]

Hinterberger, T., Wilhelm, B., Veit, R., Weiskopf, N., Lal, TN., Birbaumer, N. Neural mechanisms underlying control of a Brain-Computer-Interface (BCI): Simultaneous recording of bold-response and EEG 2004 (poster)

[BibTex]

Masking by plaid patterns revisited

Wichmann, F.

Experimentelle Psychologie. Beitr{\"a}ge zur 46. Tagung experimentell arbeitender Psychologen, 46, pages: 285, 2004 (poster)

[BibTex]

Wichmann, F. Masking by plaid patterns revisited Experimentelle Psychologie. Beitr{\"a}ge zur 46. Tagung experimentell arbeitender Psychologen, 46, pages: 285, 2004 (poster)

[BibTex]

Early visual processing—data, theory, models

Wichmann, F.

Experimentelle Psychologie. Beitr{\"a}ge zur 46. Tagung experimentell arbeitender Psychologen, 46, pages: 24, 2004 (poster)

[BibTex]

Wichmann, F. Early visual processing—data, theory, models Experimentelle Psychologie. Beitr{\"a}ge zur 46. Tagung experimentell arbeitender Psychologen, 46, pages: 24, 2004 (poster)

[BibTex]

Implicit Wiener series for capturing higher-order interactions in images

Franz, M., Schölkopf, B.

Sensory coding and the natural environment, (Editors: Olshausen, B.A. and M. Lewicki), 2004 (poster)

Abstract

The information about the objects in an image is almost exclusively described by the higher-order interactions of its pixels. The Wiener series is one of the standard methods to systematically characterize these interactions. However, the classical estimation method of the Wiener expansion coefficients via cross-correlation suffers from severe problems that prevent its application to high-dimensional and strongly nonlinear signals such as images. We propose an estimation method based on regression in a reproducing kernel Hilbert space that overcomes these problems using polynomial kernels as known from Support Vector Machines and other kernel-based methods. Numerical experiments show performance advantages in terms of convergence, interpretability and system sizes that can be handled. By the time of the conference, we will be able to present first results on the higher-order structure of natural images.

[BibTex]

Franz, M., Schölkopf, B. Implicit Wiener series for capturing higher-order interactions in images Sensory coding and the natural environment, (Editors: Olshausen, B.A. and M. Lewicki), 2004 (poster)

[BibTex]

Classification and Memory Behaviour of Man Revisited by Machine

Graf, A., Wichmann, F., Bülthoff, H., Schölkopf, B.

CSHL Meeting on Computational & Systems Neuroscience (COSYNE), 2004 (poster)

[BibTex]

Graf, A., Wichmann, F., Bülthoff, H., Schölkopf, B. Classification and Memory Behaviour of Man Revisited by Machine CSHL Meeting on Computational & Systems Neuroscience (COSYNE), 2004 (poster)

[BibTex]

2002

Real-Time Statistical Learning for Oculomotor Control and Visuomotor Coordination

Vijayakumar, S., Souza, A., Peters, J., Conradt, J., Rutkowski, T., Ijspeert, A., Nakanishi, J., Inoue, M., Shibata, T., Wiryo, A., Itti, L., Amari, S., Schaal, S.

(Editors: Becker, S. , S. Thrun, K. Obermayer), Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), December 2002 (poster)

Web [BibTex]

2002

Vijayakumar, S., Souza, A., Peters, J., Conradt, J., Rutkowski, T., Ijspeert, A., Nakanishi, J., Inoue, M., Shibata, T., Wiryo, A., Itti, L., Amari, S., Schaal, S. Real-Time Statistical Learning for Oculomotor Control and Visuomotor Coordination (Editors: Becker, S. , S. Thrun, K. Obermayer), Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), December 2002 (poster)

Web [BibTex]

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.

Web DOI [BibTex]

Rosas, P., Wichmann, F., Wagemans, J. Surface-slant-from-texture discrimination: Effects of slant level and texture type Journal of Vision, 2(7):300, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)

Web DOI [BibTex]

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.

Web DOI [BibTex]

Wichmann, F. Modelling Contrast Transfer in Spatial Vision Journal of Vision, 2(10):7, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)

Web DOI [BibTex]

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.

Web DOI [BibTex]

Henning, G., Wichmann, F., Bird, C. Pulse train detection and discrimination in pink noise Journal of Vision, 2(7):229, Second Annual Meeting of the Vision Sciences Society (VSS), November 2002 (poster)

Web DOI [BibTex]

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.

Web [BibTex]

Braun, D., Wichmann, F., Gegenfurtner, K. Phase information in the recognition of natural images Perception, 31(ECVP Abstract Supplement):133, 25th European Conference on Visual Perception, August 2002 (poster)

Web [BibTex]

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.

Web [BibTex]

Wichmann, F., Henning, G. Detection and discrimination in pink noise 5, pages: 100, 5. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2002 (poster)

Web [BibTex]

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).

[BibTex]

Wichmann, F. Application of Monte Carlo Methods to Psychometric Function Fitting Proceedings of the 33rd European Conference on Mathematical Psychology, pages: 44, 2002 (poster)

[BibTex]

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.

PDF [BibTex]

Franz, MO. Optimal linear estimation of self-motion - a real-world test of a model of fly tangential neurons 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)

PDF [BibTex]

1996

Aktives Erwerben eines Ansichtsgraphen zur diskreten Repräsentation offener Umwelten.

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

Fortschritte der K{\"u}nstlichen Intelligenz, pages: 138-147, (Editors: M. Thielscher and S.-E. Bornscheuer), 1996 (poster)

PDF PostScript [BibTex]

1996

Franz, M., Schölkopf, B., Mallot, H., Bülthoff, H. Aktives Erwerben eines Ansichtsgraphen zur diskreten Repräsentation offener Umwelten. Fortschritte der K{\"u}nstlichen Intelligenz, pages: 138-147, (Editors: M. Thielscher and S.-E. Bornscheuer), 1996 (poster)

PDF PostScript [BibTex]

Does motion-blur facilitate motion detection ?

Wichmann, F., Henning, G.

OSA Conference Program, pages: S127, 1996 (poster)

Abstract

Retinal-image motion induces the perceptual loss of high spatial-frequency content - motion blur - that affects broadband stimuli. The relative detectability of motion blur and motion itself, measured in 2-AFC experiments, shows that, although the blur associated with motion can be detected, motion itself is the more effective cue.

[BibTex]

Wichmann, F., Henning, G. Does motion-blur facilitate motion detection ? OSA Conference Program, pages: S127, 1996 (poster)

[BibTex]

1995

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.

[BibTex]

1995

Wichmann, F., Henning, G. Image segmentation from motion: just the loss of high-spatial-frequency content ? Perception, 24, pages: S19, 1995 (poster)

[BibTex]

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