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2016


Thumb xl psychscience
Creating body shapes from verbal descriptions by linking similarity spaces

Hill, M. Q., Streuber, S., Hahn, C. A., Black, M. J., O’Toole, A. J.

Psychological Science, 27(11):1486-1497, November 2016, (article)

Abstract
Brief verbal descriptions of bodies (e.g. curvy, long-legged) can elicit vivid mental images. The ease with which we create these mental images belies the complexity of three-dimensional body shapes. We explored the relationship between body shapes and body descriptions and show that a small number of words can be used to generate categorically accurate representations of three-dimensional bodies. The dimensions of body shape variation that emerged in a language-based similarity space were related to major dimensions of variation computed directly from three-dimensional laser scans of 2094 bodies. This allowed us to generate three-dimensional models of people in the shape space using only their coordinates on analogous dimensions in the language-based description space. Human descriptions of photographed bodies and their corresponding models matched closely. The natural mapping between the spaces illustrates the role of language as a concise code for body shape, capturing perceptually salient global and local body features.

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pdf [BibTex]

2016


pdf [BibTex]


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Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G.

Journal of Intelligent & Robotic Systems, 83(3-4):393-408, (Editors: Luis Almeida, Lino Marques ), September 2016, Special Issue: Autonomous Robot Systems (article)

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DOI [BibTex]

DOI [BibTex]


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Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills

Maeda, G., Ewerton, M., Koert, D., Peters, J.

IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Body Talk: Crowdshaping Realistic 3D Avatars with Words

Streuber, S., Quiros-Ramirez, M. A., Hill, M. Q., Hahn, C. A., Zuffi, S., O’Toole, A., Black, M. J.

ACM Trans. Graph. (Proc. SIGGRAPH), 35(4):54:1-54:14, July 2016 (article)

Abstract
Realistic, metrically accurate, 3D human avatars are useful for games, shopping, virtual reality, and health applications. Such avatars are not in wide use because solutions for creating them from high-end scanners, low-cost range cameras, and tailoring measurements all have limitations. Here we propose a simple solution and show that it is surprisingly accurate. We use crowdsourcing to generate attribute ratings of 3D body shapes corresponding to standard linguistic descriptions of 3D shape. We then learn a linear function relating these ratings to 3D human shape parameters. Given an image of a new body, we again turn to the crowd for ratings of the body shape. The collection of linguistic ratings of a photograph provides remarkably strong constraints on the metric 3D shape. We call the process crowdshaping and show that our Body Talk system produces shapes that are perceptually indistinguishable from bodies created from high-resolution scans and that the metric accuracy is sufficient for many tasks. This makes body “scanning” practical without a scanner, opening up new applications including database search, visualization, and extracting avatars from books.

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pdf web tool video talk (ppt) [BibTex]

pdf web tool video talk (ppt) [BibTex]


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Capturing Hands in Action using Discriminative Salient Points and Physics Simulation

Tzionas, D., Ballan, L., Srikantha, A., Aponte, P., Pollefeys, M., Gall, J.

International Journal of Computer Vision (IJCV), 118(2):172-193, June 2016 (article)

Abstract
Hand motion capture is a popular research field, recently gaining more attention due to the ubiquity of RGB-D sensors. However, even most recent approaches focus on the case of a single isolated hand. In this work, we focus on hands that interact with other hands or objects and present a framework that successfully captures motion in such interaction scenarios for both rigid and articulated objects. Our framework combines a generative model with discriminatively trained salient points to achieve a low tracking error and with collision detection and physics simulation to achieve physically plausible estimates even in case of occlusions and missing visual data. Since all components are unified in a single objective function which is almost everywhere differentiable, it can be optimized with standard optimization techniques. Our approach works for monocular RGB-D sequences as well as setups with multiple synchronized RGB cameras. For a qualitative and quantitative evaluation, we captured 29 sequences with a large variety of interactions and up to 150 degrees of freedom.

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Website pdf link (url) DOI Project Page [BibTex]

Website pdf link (url) DOI Project Page [BibTex]


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On estimation of functional causal models: General results and application to post-nonlinear causal model

Zhang, K., Wang, Z., Zhang, J., Schölkopf, B.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Human Pose Estimation from Video and IMUs

Marcard, T. V., Pons-Moll, G., Rosenhahn, B.

Transactions on Pattern Analysis and Machine Intelligence PAMI, 38(8):1533-1547, January 2016 (article)

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data pdf dataset_documentation [BibTex]

data pdf dataset_documentation [BibTex]


Thumb xl cloud tracking
Gaussian Process-Based Predictive Control for Periodic Error Correction

Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P.

IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Townsend, J., Koep, N., Weichwald, S.

Journal of Machine Learning Research, 17(137):1-5, 2016 (article)

ei

PDF Arxiv Code Project page link (url) [BibTex]


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A Causal, Data-driven Approach to Modeling the Kepler Data

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

Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Probabilistic Inference for Determining Options in Reinforcement Learning

Daniel, C., van Hoof, H., Peters, J., Neumann, G.

Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Moving-horizon Nonlinear Least Squares-based Multirobot Cooperative Perception

Ahmad, A., Bülthoff, H.

Robotics and Autonomous Systems, 83, pages: 275-286, 2016 (article)

Abstract
In this article we present an online estimator for multirobot cooperative localization and target tracking based on nonlinear least squares minimization. Our method not only makes the rigorous optimization-based approach applicable online but also allows the estimator to be stable and convergent. We do so by employing a moving horizon technique to nonlinear least squares minimization and a novel design of the arrival cost function that ensures stability and convergence of the estimator. Through an extensive set of real robot experiments, we demonstrate the robustness of our method as well as the optimality of the arrival cost function. The experiments include comparisons of our method with i) an extended Kalman filter-based online-estimator and ii) an offline-estimator based on full-trajectory nonlinear least squares.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Influence of initial fixation position in scene viewing

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R.

Vision Research, 129, pages: 33-49, 2016 (article)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Testing models of peripheral encoding using metamerism in an oddity paradigm

Wallis, T. S. A., Bethge, M., Wichmann, F. A.

Journal of Vision, 16(2), 2016 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Modeling Confounding by Half-Sibling Regression

Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J.

Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)

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Code link (url) DOI Project Page [BibTex]

Code link (url) DOI Project Page [BibTex]


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Dual Control for Approximate Bayesian Reinforcement Learning

Klenske, E. D., Hennig, P.

Journal of Machine Learning Research, 17(127):1-30, 2016 (article)

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PDF link (url) [BibTex]

PDF link (url) [BibTex]


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A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes

Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J.

Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl siyong
Shape estimation of subcutaneous adipose tissue using an articulated statistical shape model

Yeo, S. Y., Romero, J., Loper, M., Machann, J., Black, M.

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 0(0):1-8, 2016 (article)

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publisher website preprint pdf link (url) DOI Project Page [BibTex]

publisher website preprint pdf link (url) DOI Project Page [BibTex]


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Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data

Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A.

Vision Research, 122, pages: 105-123, 2016 (article)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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On designing an active tail for legged robots: simplifying control via decoupling of control objectives

Heim, S. W., Ajallooeian, M., Eckert, P., Vespignani, M., Ijspeert, A. J.

Industrial Robot: An International Journal, 43, pages: 338-346, Emerald Group Publishing Limited, 2016 (article)

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Preprint [BibTex]

Preprint [BibTex]


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NimbRo Explorer: Semi-Autonomous Exploration and Mobile Manipulation in Rough Terrain

Stueckler, J., Schwarz, M., Schadler, M., Topalidou-Kyniazopoulou, A., Behnke, S.

Journal of Field Robotics (JFR), 33(4):411-430, Wiley, 2016 (article)

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[BibTex]

[BibTex]


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Hierarchical Relative Entropy Policy Search

Daniel, C., Neumann, G., Kroemer, O., Peters, J.

Journal of Machine Learning Research, 17(93):1-50, 2016 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Kernel Mean Shrinkage Estimators

Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B.

Journal of Machine Learning Research, 17(48):1-41, 2016 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


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Learning to Deblur

Schuler, C. J., Hirsch, M., Harmeling, S., Schölkopf, B.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7):1439-1451, IEEE, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Transfer Learning in Brain-Computer Interfaces

Jayaram, V., Alamgir, M., Altun, Y., Schölkopf, B., Grosse-Wentrup, M.

IEEE Computational Intelligence Magazine, 11(1):20-31, 2016 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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MERLiN: Mixture Effect Recovery in Linear Networks

Weichwald, S., Grosse-Wentrup, M., Gretton, A.

IEEE Journal of Selected Topics in Signal Processing, 10(7):1254-1266, 2016 (article)

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Arxiv Code PDF DOI Project Page [BibTex]

Arxiv Code PDF DOI Project Page [BibTex]


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Causal inference using invariant prediction: identification and confidence intervals

Peters, J., Bühlmann, P., Meinshausen, N.

Journal of the Royal Statistical Society, Series B (Statistical Methodology), 78(5):947-1012, 2016, (with discussion) (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Causal discovery and inference: concepts and recent methodological advances

Spirtes, P., Zhang, K.

Applied Informatics, 3(3):1-28, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of Neural Engineering, 13(6):066021, 2016 (article)

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link (url) Project Page [BibTex]


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ATRIAS: Design and validation of a tether-free 3D-capable spring-mass bipedal robot

Hubicki, C., Grimes, J., Jones, M., Renjewski, D., Spröwitz, A., Abate, A., Hurst, J.

{The International Journal of Robotics Research}, 35(12):1497-1521, Sage Publications, Inc., Cambridge, MA, 2016 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Influence Estimation and Maximization in Continuous-Time Diffusion Networks

Gomez-Rodriguez, M., Song, L., Du, N., Zha, H., Schölkopf, B.

ACM Transactions on Information Systems, 34(2):9:1-9:33, 2016 (article)

ei

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


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Multi-Layered Mapping and Navigation for Autonomous Micro Aerial Vehicles

Droeschel, D., Nieuwenhuisen, M., Beul, M., Stueckler, J., Holz, D., Behnke, S.

Journal of Field Robotics (JFR), 33(4):451-475, 2016 (article)

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[BibTex]

[BibTex]


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The population of long-period transiting exoplanets

Foreman-Mackey, D., Morton, T. D., Hogg, D. W., Agol, E., Schölkopf, B.

The Astronomical Journal, 152(6):206, 2016 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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An overview of quantitative approaches in Gestalt perception

Jäkel, F., Singh, M., Wichmann, F. A., Herzog, M. H.

Vision Research, 126, pages: 3-8, 2016 (article)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Bootstrat: Population Informed Bootstrapping for Rare Variant Tests

Huang, H., Peloso, G. M., Howrigan, D., Rakitsch, B., Simon-Gabriel, C. J., Goldstein, J. I., Daly, M. J., Borgwardt, K., Neale, B. M.

bioRxiv, 2016, preprint (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control

Rueckert, E., Camernik, J., Peters, J., Babic, J.

Nature PG: Scientific Reports, 6(Article number: 28455), 2016 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Learning Taxonomy Adaptation in Large-scale Classification

Babbar, R., Partalas, I., Gaussier, E., Amini, M., Amblard, C.

Journal of Machine Learning Research, 17(98):1-37, 2016 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Thumb xl screen shot 2016 02 22 at 11.46.41
The GRASP Taxonomy of Human Grasp Types

Feix, T., Romero, J., Schmiedmayer, H., Dollar, A., Kragic, D.

Human-Machine Systems, IEEE Transactions on, 46(1):66-77, 2016 (article)

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publisher website pdf DOI Project Page [BibTex]

publisher website pdf DOI Project Page [BibTex]


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BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors

Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A., Obermayer, K.

Frontiers in Psychology, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Preface to the ACM TIST Special Issue on Causal Discovery and Inference

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 17, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl pami
Map-Based Probabilistic Visual Self-Localization

Brubaker, M. A., Geiger, A., Urtasun, R.

IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)

Abstract
Accurate and efficient self-localization is a critical problem for autonomous systems. This paper describes an affordable solution to vehicle self-localization which uses odometry computed from two video cameras and road maps as the sole inputs. The core of the method is a probabilistic model for which an efficient approximate inference algorithm is derived. The inference algorithm is able to utilize distributed computation in order to meet the real-time requirements of autonomous systems in some instances. Because of the probabilistic nature of the model the method is capable of coping with various sources of uncertainty including noise in the visual odometry and inherent ambiguities in the map (e.g., in a Manhattan world). By exploiting freely available, community developed maps and visual odometry measurements, the proposed method is able to localize a vehicle to 4m on average after 52 seconds of driving on maps which contain more than 2,150km of drivable roads.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Recurrent Spiking Networks Solve Planning Tasks

Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., Peters, J.

Nature PG: Scientific Reports, 6(Article number: 21142), 2016 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid

Herzog, A., Rotella, N., Mason, S., Grimminger, F., Schaal, S., Righetti, L.

Autonomous Robots, 40(3):473-491, 2016 (article)

Abstract
Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.

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link (url) DOI [BibTex]


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Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations

Genewein, T, Braun, DA

Biological Cybernetics, 110(2):135–150, June 2016 (article)

Abstract
Bayesian inference and bounded rational decision-making require the accumulation of evidence or utility, respectively, to transform a prior belief or strategy into a posterior probability distribution over hypotheses or actions. Crucially, this process cannot be simply realized by independent integrators, since the different hypotheses and actions also compete with each other. In continuous time, this competitive integration process can be described by a special case of the replicator equation. Here we investigate simple analog electric circuits that implement the underlying differential equation under the constraint that we only permit a limited set of building blocks that we regard as biologically interpretable, such as capacitors, resistors, voltage-dependent conductances and voltage- or current-controlled current and voltage sources. The appeal of these circuits is that they intrinsically perform normalization without requiring an explicit divisive normalization. However, even in idealized simulations, we find that these circuits are very sensitive to internal noise as they accumulate error over time. We discuss in how far neural circuits could implement these operations that might provide a generic competitive principle underlying both perception and action.

ei

DOI [BibTex]

DOI [BibTex]