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2014


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Human Pose Estimation: New Benchmark and State of the Art Analysis

Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3686 - 3693, IEEE, IEEE International Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)

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pdf DOI Project Page Project Page Project Page [BibTex]

2014


pdf DOI Project Page Project Page Project Page [BibTex]


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FAUST: Dataset and evaluation for 3D mesh registration

(Dataset Award, Eurographics Symposium on Geometry Processing (SGP), 2016)

Bogo, F., Romero, J., Loper, M., Black, M. J.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3794 -3801, Columbus, Ohio, USA, IEEE International Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)

Abstract
New scanning technologies are increasing the importance of 3D mesh data and the need for algorithms that can reliably align it. Surface registration is important for building full 3D models from partial scans, creating statistical shape models, shape retrieval, and tracking. The problem is particularly challenging for non-rigid and articulated objects like human bodies. While the challenges of real-world data registration are not present in existing synthetic datasets, establishing ground-truth correspondences for real 3D scans is difficult. We address this with a novel mesh registration technique that combines 3D shape and appearance information to produce high-quality alignments. We define a new dataset called FAUST that contains 300 scans of 10 people in a wide range of poses together with an evaluation methodology. To achieve accurate registration, we paint the subjects with high-frequency textures and use an extensive validation process to ensure accurate ground truth. We find that current shape registration methods have trouble with this real-world data. The dataset and evaluation website are available for research purposes at http://faust.is.tue.mpg.de.

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pdf Video Dataset Poster Talk DOI Project Page Project Page Project Page [BibTex]

pdf Video Dataset Poster Talk DOI Project Page Project Page Project Page [BibTex]


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Model Transport: Towards Scalable Transfer Learning on Manifolds

Freifeld, O., Hauberg, S., Black, M. J.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1378 -1385, Columbus, Ohio, USA, IEEE Intenational Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)

Abstract
We consider the intersection of two research fields: transfer learning and statistics on manifolds. In particular, we consider, for manifold-valued data, transfer learning of tangent-space models such as Gaussians distributions, PCA, regression, or classifiers. Though one would hope to simply use ordinary Rn-transfer learning ideas, the manifold structure prevents it. We overcome this by basing our method on inner-product-preserving parallel transport, a well-known tool widely used in other problems of statistics on manifolds in computer vision. At first, this straightforward idea seems to suffer from an obvious shortcoming: Transporting large datasets is prohibitively expensive, hindering scalability. Fortunately, with our approach, we never transport data. Rather, we show how the statistical models themselves can be transported, and prove that for the tangent-space models above, the transport “commutes” with learning. Consequently, our compact framework, applicable to a large class of manifolds, is not restricted by the size of either the training or test sets. We demonstrate the approach by transferring PCA and logistic-regression models of real-world data involving 3D shapes and image descriptors.

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pdf SupMat Video poster DOI Project Page [BibTex]

pdf SupMat Video poster DOI Project Page [BibTex]


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Robot Arm Pose Estimation through Pixel-Wise Part Classification

Bohg, J., Romero, J., Herzog, A., Schaal, S.

In IEEE International Conference on Robotics and Automation (ICRA) 2014, pages: 3143-3150, IEEE International Conference on Robotics and Automation (ICRA), June 2014 (inproceedings)

Abstract
We propose to frame the problem of marker-less robot arm pose estimation as a pixel-wise part classification problem. As input, we use a depth image in which each pixel is classified to be either from a particular robot part or the background. The classifier is a random decision forest trained on a large number of synthetically generated and labeled depth images. From all the training samples ending up at a leaf node, a set of offsets is learned that votes for relative joint positions. Pooling these votes over all foreground pixels and subsequent clustering gives us an estimate of the true joint positions. Due to the intrinsic parallelism of pixel-wise classification, this approach can run in super real-time and is more efficient than previous ICP-like methods. We quantitatively evaluate the accuracy of this approach on synthetic data. We also demonstrate that the method produces accurate joint estimates on real data despite being purely trained on synthetic data.

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video code pdf DOI Project Page [BibTex]

video code pdf DOI Project Page [BibTex]


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Nanopropellers and Their Actuation in Complex Viscoelastic Media

Schamel, D., Mark, A. G., Gibbs, J. G., Miksch, C., Morozov, K. I., Leshansky, A. M., Fischer, P.

ACS Nano, 8(9):8794-8801, June 2014, Featured cover article. (article)

Abstract
Tissue and biological fluids are complex viscoelastic media with a nanoporous macromolecular structure. Here, we demonstrate that helical nanopropellers can be controllably steered through such a biological gel. The screw-propellers have a filament diameter of about 70 nm and are smaller than previously reported nanopropellers as well as any swimming microorganism. We show that the nanoscrews will move through high-viscosity solutions with comparable velocities to that of larger micropropellers, even though they are so small that Brownian forces suppress their actuation in pure water. When actuated in viscoelastic hyaluronan gels, the nanopropellers appear to have a significant advantage, as they are of the same size range as the gel’s mesh size. Whereas larger helices will show very low or negligible propulsion in hyaluronan solutions, the nanoscrews actually display significantly enhanced propulsion velocities that exceed the highest measured speeds in Newtonian fluids. The nanopropellers are not only promising for applications in the extracellular environment but small enough to be taken up by cells.

Featured cover article.

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Video - Helical Micro and Nanopropellers for Applications in Biological Fluidic Environments link (url) DOI [BibTex]


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Efficient Non-linear Markov Models for Human Motion

Lehrmann, A. M., Gehler, P. V., Nowozin, S.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 1314-1321, IEEE, IEEE International Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)

Abstract
Dynamic Bayesian networks such as Hidden Markov Models (HMMs) are successfully used as probabilistic models for human motion. The use of hidden variables makes them expressive models, but inference is only approximate and requires procedures such as particle filters or Markov chain Monte Carlo methods. In this work we propose to instead use simple Markov models that only model observed quantities. We retain a highly expressive dynamic model by using interactions that are nonlinear and non-parametric. A presentation of our approach in terms of latent variables shows logarithmic growth for the computation of exact loglikelihoods in the number of latent states. We validate our model on human motion capture data and demonstrate state-of-the-art performance on action recognition and motion completion tasks.

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Project page pdf DOI Project Page [BibTex]

Project page pdf DOI Project Page [BibTex]


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Grassmann Averages for Scalable Robust PCA

Hauberg, S., Feragen, A., Black, M. J.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3810 -3817, Columbus, Ohio, USA, IEEE International Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)

Abstract
As the collection of large datasets becomes increasingly automated, the occurrence of outliers will increase – "big data" implies "big outliers". While principal component analysis (PCA) is often used to reduce the size of data, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA do not scale beyond small-to-medium sized datasets. To address this, we introduce the Grassmann Average (GA), which expresses dimensionality reduction as an average of the subspaces spanned by the data. Because averages can be efficiently computed, we immediately gain scalability. GA is inherently more robust than PCA, but we show that they coincide for Gaussian data. We exploit that averages can be made robust to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. Robustness can be with respect to vectors (subspaces) or elements of vectors; we focus on the latter and use a trimmed average. The resulting Trimmed Grassmann Average (TGA) is particularly appropriate for computer vision because it is robust to pixel outliers. The algorithm has low computational complexity and minimal memory requirements, making it scalable to "big noisy data." We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie.

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pdf code supplementary material tutorial video results video talk poster DOI Project Page [BibTex]

pdf code supplementary material tutorial video results video talk poster DOI Project Page [BibTex]


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Posebits for Monocular Human Pose Estimation

Pons-Moll, G., Fleet, D. J., Rosenhahn, B.

In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2345-2352, Columbus, Ohio, USA, IEEE International Conference on Computer Vision and Pattern Recognition, June 2014 (inproceedings)

Abstract
We advocate the inference of qualitative information about 3D human pose, called posebits, from images. Posebits represent boolean geometric relationships between body parts (e.g., left-leg in front of right-leg or hands close to each other). The advantages of posebits as a mid-level representation are 1) for many tasks of interest, such qualitative pose information may be sufficient (e.g. , semantic image retrieval), 2) it is relatively easy to annotate large image corpora with posebits, as it simply requires answers to yes/no questions; and 3) they help resolve challenging pose ambiguities and therefore facilitate the difficult talk of image-based 3D pose estimation. We introduce posebits, a posebit database, a method for selecting useful posebits for pose estimation and a structural SVM model for posebit inference. Experiments show the use of posebits for semantic image retrieval and for improving 3D pose estimation.

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pdf Project Page Project Page [BibTex]

pdf Project Page Project Page [BibTex]


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A Data-driven Approach to Remote Tactile Interaction: From a BioTac Sensor to Any Fingertip Cutaneous Device

Pacchierotti, C., Prattichizzo, D., Kuchenbecker, K. J.

In Haptics: Neuroscience, Devices, Modeling, and Applications, Proc. EuroHaptics, Part I, 8618, pages: 418-424, Lecture Notes in Computer Science, Springer-Verlag, Berlin Heidelberg, June 2014, Poster presentation given by Pacchierotti in Versailles, France (inproceedings)

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[BibTex]

[BibTex]


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Evaluating the BioTac’s Ability to Detect and Characterize Lumps in Simulated Tissue

Hui, J. C. T., Kuchenbecker, K. J.

In Haptics: Neuroscience, Devices, Modeling, and Applications, Proc. EuroHaptics, Part II, 8619, pages: 295-302, Lecture Notes in Computer Science, Springer-Verlag, Berlin Heidelberg, June 2014, Poster presentation given by Hui in Versailles, France (inproceedings)

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[BibTex]

[BibTex]


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Simultaneous Underwater Visibility Assessment, Enhancement and Improved Stereo

Roser, M., Dunbabin, M., Geiger, A.

IEEE International Conference on Robotics and Automation, pages: 3840 - 3847 , Hong Kong, China, IEEE International Conference on Robotics and Automation, June 2014 (conference)

Abstract
Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows real-time implementation onboard an Autonomous Underwater Vehicles for improved navigation and obstacle avoidance performance.

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pdf DOI [BibTex]

pdf DOI [BibTex]


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Preserving Modes and Messages via Diverse Particle Selection

Pacheco, J., Zuffi, S., Black, M. J., Sudderth, E.

In Proceedings of the 31st International Conference on Machine Learning (ICML-14), 32(1):1152-1160, J. Machine Learning Research Workshop and Conf. and Proc., Beijing, China, International Conference on Machine Learning (ICML), June 2014 (inproceedings)

Abstract
In applications of graphical models arising in domains such as computer vision and signal processing, we often seek the most likely configurations of high-dimensional, continuous variables. We develop a particle-based max-product algorithm which maintains a diverse set of posterior mode hypotheses, and is robust to initialization. At each iteration, the set of hypotheses at each node is augmented via stochastic proposals, and then reduced via an efficient selection algorithm. The integer program underlying our optimization-based particle selection minimizes errors in subsequent max-product message updates. This objective automatically encourages diversity in the maintained hypotheses, without requiring tuning of application-specific distances among hypotheses. By avoiding the stochastic resampling steps underlying particle sum-product algorithms, we also avoid common degeneracies where particles collapse onto a single hypothesis. Our approach significantly outperforms previous particle-based algorithms in experiments focusing on the estimation of human pose from single images.

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pdf SupMat link (url) Project Page Project Page [BibTex]

pdf SupMat link (url) Project Page Project Page [BibTex]


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Teaching Forward and Inverse Kinematics of Robotic Manipulators Via MATLAB

Wong, D., Dames, P., J. Kuchenbecker, K.

June 2014, Presented at {\em ICRA Workshop on {MATLAB/Simulink} for Robotics Education and Research}. Oral presentation given by {Dames} and {Wong} (misc)

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[BibTex]

[BibTex]


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Calibrating and Centering Quasi-Central Catadioptric Cameras

Schoenbein, M., Strauss, T., Geiger, A.

IEEE International Conference on Robotics and Automation, pages: 4443 - 4450, Hong Kong, China, IEEE International Conference on Robotics and Automation, June 2014 (conference)

Abstract
Non-central catadioptric models are able to cope with irregular camera setups and inaccuracies in the manufacturing process but are computationally demanding and thus not suitable for robotic applications. On the other hand, calibrating a quasi-central (almost central) system with a central model introduces errors due to a wrong relationship between the viewing ray orientations and the pixels on the image sensor. In this paper, we propose a central approximation to quasi-central catadioptric camera systems that is both accurate and efficient. We observe that the distance to points in 3D is typically large compared to deviations from the single viewpoint. Thus, we first calibrate the system using a state-of-the-art non-central camera model. Next, we show that by remapping the observations we are able to match the orientation of the viewing rays of a much simpler single viewpoint model with the true ray orientations. While our approximation is general and applicable to all quasi-central camera systems, we focus on one of the most common cases in practice: hypercatadioptric cameras. We compare our model to a variety of baselines in synthetic and real localization and motion estimation experiments. We show that by using the proposed model we are able to achieve near non-central accuracy while obtaining speed-ups of more than three orders of magnitude compared to state-of-the-art non-central models.

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pdf DOI [BibTex]

pdf DOI [BibTex]


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Convertor

Fischer, P., Mark, A.

May 2014 (patent)

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[BibTex]

[BibTex]


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Nonmyopic View Planning for Active Object Classification and Pose Estimation

Atanasov, N., Sankaran, B., Le Ny, J., Pappas, G., Daniilidis, K.

IEEE Transactions on Robotics, May 2014, clmc (article)

Abstract
One of the central problems in computer vision is the detection of semantically important objects and the estimation of their pose. Most of the work in object detection has been based on single image processing and its performance is limited by occlusions and ambiguity in appearance and geometry. This paper proposes an active approach to object detection by controlling the point of view of a mobile depth camera. When an initial static detection phase identifies an object of interest, several hypotheses are made about its class and orientation. The sensor then plans a sequence of viewpoints, which balances the amount of energy used to move with the chance of identifying the correct hypothesis. We formulate an active M-ary hypothesis testing problem, which includes sensor mobility, and solve it using a point-based approximate POMDP algorithm. The validity of our approach is verified through simulation and real-world experiments with the PR2 robot. The results suggest a significant improvement over static object detection

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Web pdf link (url) [BibTex]

Web pdf link (url) [BibTex]


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3D Traffic Scene Understanding from Movable Platforms

Geiger, A., Lauer, M., Wojek, C., Stiller, C., Urtasun, R.

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 36(5):1012-1025, published, IEEE, Los Alamitos, CA, May 2014 (article)

Abstract
In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow and occupancy grids. For each of these cues we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

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pdf link (url) [BibTex]

pdf link (url) [BibTex]


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Modeling the Human Body in 3D: Data Registration and Human Shape Representation

Tsoli, A.

Brown University, Department of Computer Science, May 2014 (phdthesis)

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pdf [BibTex]

pdf [BibTex]


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Model transport: towards scalable transfer learning on manifolds - supplemental material

Freifeld, O., Hauberg, S., Black, M. J.

(9), April 2014 (techreport)

Abstract
This technical report is complementary to "Model Transport: Towards Scalable Transfer Learning on Manifolds" and contains proofs, explanation of the attached video (visualization of bases from the body shape experiments), and high-resolution images of select results of individual reconstructions from the shape experiments. It is identical to the supplemental mate- rial submitted to the Conference on Computer Vision and Pattern Recognition (CVPR 2014) on November 2013.

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PDF [BibTex]


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Efficient demagnetization cooling of atoms and its limits

Volchkov, V., Rührig, J., Pfau, T., Griesmaier, A.

Physical Review A, 89, pages: 043417, American Physical Society (APS), April 2014 (article)

Abstract
Demagnetization cooling relies on spin-orbit coupling that brings motional and spin degrees of freedom into thermal equilibrium. In the case of a gas, one has the advantage that the spin degree of freedom can be cooled very efficiently using optical pumping. We investigate demagnetization cooling of a chromium gas in a deep optical dipole trap over a large temperature range and reach high densities up to 5×10^19 m^−3. We study the loss mechanism under such extreme conditions and identify excited-state collisions as the main limiting process. We discuss that in some systems demagnetization cooling has a realistic potential of reaching degeneracy by optical cooling only.

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DOI [BibTex]

DOI [BibTex]


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Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics

Hennig, P., Hauberg, S.

In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, AISTATS, April 2014 (inproceedings)

Abstract
We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian manifolds, where non-analytic ordinary differential equations are involved in virtually all computations. The probabilistic formulation permits marginalising the uncertainty of the numerical solution such that statistics are less sensitive to inaccuracies. This leads to new Riemannian algorithms for mean value computations and principal geodesic analysis. Marginalisation also means results can be less precise than point estimates, enabling a noticeable speed-up over the state of the art. Our approach is an argument for a wider point that uncertainty caused by numerical calculations should be tracked throughout the pipeline of machine learning algorithms.

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pdf Youtube Supplements Project page link (url) [BibTex]

pdf Youtube Supplements Project page link (url) [BibTex]


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Method and device for blind correction of optical aberrations in a digital image

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

International Patent Application, No. PCT/EP2012/068868, April 2014 (patent)

ei

[BibTex]


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Data-Driven Grasp Synthesis - A Survey

Bohg, J., Morales, A., Asfour, T., Kragic, D.

IEEE Transactions on Robotics, 30, pages: 289 - 309, IEEE, April 2014 (article)

Abstract
We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps. We divide the approaches into three groups based on whether they synthesize grasps for known, familiar or unknown objects. This structure allows us to identify common object representations and perceptual processes that facilitate the employed data-driven grasp synthesis technique. In the case of known objects, we concentrate on the approaches that are based on object recognition and pose estimation. In the case of familiar objects, the techniques use some form of a similarity matching to a set of previously encountered objects. Finally for the approaches dealing with unknown objects, the core part is the extraction of specific features that are indicative of good grasps. Our survey provides an overview of the different methodologies and discusses open problems in the area of robot grasping. We also draw a parallel to the classical approaches that rely on analytic formulations.

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PDF link (url) DOI Project Page [BibTex]

PDF link (url) DOI Project Page [BibTex]


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Multi-View Priors for Learning Detectors from Sparse Viewpoint Data

Pepik, B., Stark, M., Gehler, P., Schiele, B.

International Conference on Learning Representations, International Conference on Learning Representations (ICLR), April 2014 (conference)

Abstract
While the majority of today's object class models provide only 2D bounding boxes, far richer output hypotheses are desirable including viewpoint, fine-grained category, and 3D geometry estimate. However, models trained to provide richer output require larger amounts of training data, preferably well covering the relevant aspects such as viewpoint and fine-grained categories. In this paper, we address this issue from the perspective of transfer learning, and design an object class model that explicitly leverages correlations between visual features. Specifically, our model represents prior distributions over permissible multi-view detectors in a parametric way -- the priors are learned once from training data of a source object class, and can later be used to facilitate the learning of a detector for a target class. As we show in our experiments, this transfer is not only beneficial for detectors based on basic-level category representations, but also enables the robust learning of detectors that represent classes at finer levels of granularity, where training data is typically even scarcer and more unbalanced. As a result, we report largely improved performance in simultaneous 2D object localization and viewpoint estimation on a recent dataset of challenging street scenes.

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reviews pdf Project Page [BibTex]

reviews pdf Project Page [BibTex]


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Local Gaussian Regression

Meier, F., Hennig, P., Schaal, S.

arXiv preprint, March 2014, clmc (misc)

Abstract
Abstract: Locally weighted regression was created as a nonparametric learning method that is computationally efficient, can learn from very large amounts of data and add data incrementally. An interesting feature of locally weighted regression is that it can work with ...

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Web link (url) [BibTex]

Web link (url) [BibTex]


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RoCKIn@Work in a Nutshell

Ahmad, A., Amigoni, A., Awaad, I., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Fontana, G., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schiaffonati, V., Schneider, S.

(FP7-ICT-601012 Revision 1.2), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, March 2014 (techreport)

Abstract
The main purpose of RoCKIn@Work is to foster innovation in industrial service robotics. Innovative robot applications for industry call for the capability to work interactively with humans and reduced initial programming requirements. This will open new opportunities to automate challenging manufacturing processes, even for small to medium-sized lots and highly customer-specific production requirements. Thereby, the RoCKIn competitions pave the way for technology transfer and contribute to the continued commercial competitiveness of European industry.

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[BibTex]

[BibTex]


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RoCKIn@Home in a Nutshell

Ahmad, A., Amigoni, F., Awaad, I., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Fontana, G., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schneider, S.

(FP7-ICT-601012 Revision 0.8), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, March 2014 (techreport)

Abstract
RoCKIn@Home is a competition that aims at bringing together the benefits of scientific benchmarking with the attraction of scientific competitions in the realm of domestic service robotics. The objectives are to bolster research in service robotics for home applications and to raise public awareness of the current and future capabilities of such robot systems to meet societal challenges like healthy ageing and longer independent living.

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[BibTex]

[BibTex]


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A Visual Analytics Approach to Study Anatomic Covariation

Hermann, M., Schunke, A., Schultz, T., Klein, R.

In Proceedings of IEEE Pacific Visualization 2014, pages: 161-168, March 2014 (inproceedings)

Abstract
Gaining insight into anatomic covariation helps the understanding of organismic shape variability in general and is of particular interest for delimiting morphological modules. Generation of hypotheses on structural covariation is undoubtedly a highly creative process, and as such, requires an exploratory approach. In this work we propose a new local anatomic covariance tensor which enables interactive visualizations to explore covariation at different levels of detail, stimulating rapid formation and (qualitative) evaluation of hypotheses. The effectiveness of the presented approach is demonstrated on a muCT dataset of mouse mandibles for which results from the literature are successfully reproduced, while providing a more detailed representation of covariation compared to state-of-the-art methods.

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PDF DOI [BibTex]

PDF DOI [BibTex]


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NRSfM using Local Rigidity

Rehan, A., Zaheer, A., Akhter, I., Saeed, A., Mahmood, B., Usmani, M., Khan, S.

In Proceedings Winter Conference on Applications of Computer Vision, pages: 69-74, open access, IEEE , Steamboat Springs, CO, USA, IEEE Winter Conference on Applications of Computer Vision (WACV) , March 2014 (inproceedings)

Abstract
Factorization methods for computation of nonrigid structure have limited practicality, and work well only when there is large enough camera motion between frames, with long sequences and limited or no occlusions. We show that typical nonrigid structure can often be approximated well as locally rigid sub-structures in time and space. Specifically, we assume that: 1) the structure can be approximated as rigid in a short local time window and 2) some point pairs stay relatively rigid in space, maintaining a fixed distance between them during the sequence. We first use the triangulation constraints in rigid SFM over a sliding time window to get an initial estimate of the nonrigid 3D structure. We then automatically identify relatively rigid point pairs in this structure, and use their length-constancy simultaneously with triangulation constraints to refine the structure estimate. Unlike factorization methods, the structure is estimated independent of the camera motion computation, adding to the simplicity and stability of the approach. Further, local factorization inherently handles significant natural occlusions gracefully, performing much better than the state-of-the art. We show more stable and accurate results as compared to the state-of-the art on even short sequences starting from 15 frames only, containing camera rotations as small as 2 degree and up to 50% missing data.

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link (url) [BibTex]

link (url) [BibTex]


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Fibrillar structures to reduce viscous drag on aerodynamic and hydrodynamic wall surfaces

Castillo, L., Aksak, B., Sitti, M.

March 2014, US Patent App. 14/774,767 (misc)

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[BibTex]

[BibTex]


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Analyzing Human High-Fives to Create an Effective High-Fiving Robot

Fitter, N. T., Kuchenbecker, K. J.

In Proc. ACM/IEEE International Conference on Human-Robot Interaction (HRI), pages: 156-157, Bielefeld, Germany, March 2014, Poster presentation given by Fitter (inproceedings)

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[BibTex]

[BibTex]


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Adaptive Offset Correction for Intracortical Brain Computer Interfaces

Homer, M. L., Perge, J. A., Black, M. J., Harrison, M. T., Cash, S. S., Hochberg, L. R.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 22(2):239-248, March 2014 (article)

Abstract
Intracortical brain computer interfaces (iBCIs) decode intended movement from neural activity for the control of external devices such as a robotic arm. Standard approaches include a calibration phase to estimate decoding parameters. During iBCI operation, the statistical properties of the neural activity can depart from those observed during calibration, sometimes hindering a user’s ability to control the iBCI. To address this problem, we adaptively correct the offset terms within a Kalman filter decoder via penalized maximum likelihood estimation. The approach can handle rapid shifts in neural signal behavior (on the order of seconds) and requires no knowledge of the intended movement. The algorithm, called MOCA, was tested using simulated neural activity and evaluated retrospectively using data collected from two people with tetraplegia operating an iBCI. In 19 clinical research test cases, where a nonadaptive Kalman filter yielded relatively high decoding errors, MOCA significantly reduced these errors (10.6 ± 10.1\%; p < 0.05, pairwise t-test). MOCA did not significantly change the error in the remaining 23 cases where a nonadaptive Kalman filter already performed well. These results suggest that MOCA provides more robust decoding than the standard Kalman filter for iBCIs.

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pdf DOI Project Page [BibTex]

pdf DOI Project Page [BibTex]


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Model-based Anthropometry: Predicting Measurements from 3D Human Scans in Multiple Poses

Tsoli, A., Loper, M., Black, M. J.

In Proceedings Winter Conference on Applications of Computer Vision, pages: 83-90, IEEE , IEEE Winter Conference on Applications of Computer Vision (WACV) , March 2014 (inproceedings)

Abstract
Extracting anthropometric or tailoring measurements from 3D human body scans is important for applications such as virtual try-on, custom clothing, and online sizing. Existing commercial solutions identify anatomical landmarks on high-resolution 3D scans and then compute distances or circumferences on the scan. Landmark detection is sensitive to acquisition noise (e.g. holes) and these methods require subjects to adopt a specific pose. In contrast, we propose a solution we call model-based anthropometry. We fit a deformable 3D body model to scan data in one or more poses; this model-based fitting is robust to scan noise. This brings the scan into registration with a database of registered body scans. Then, we extract features from the registered model (rather than from the scan); these include, limb lengths, circumferences, and statistical features of global shape. Finally, we learn a mapping from these features to measurements using regularized linear regression. We perform an extensive evaluation using the CAESAR dataset and demonstrate that the accuracy of our method outperforms state-of-the-art methods.

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pdf DOI Project Page Project Page [BibTex]

pdf DOI Project Page Project Page [BibTex]


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A physically-based approach to reflection separation: from physical modeling to constrained optimization

Kong, N., Tai, Y., Shin, J. S.

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 36(2):209-221, IEEE Computer Society, Febuary 2014 (article)

Abstract
We propose a physically-based approach to separate reflection using multiple polarized images with a background scene captured behind glass. The input consists of three polarized images, each captured from the same view point but with a different polarizer angle separated by 45 degrees. The output is the high-quality separation of the reflection and background layers from each of the input images. A main technical challenge for this problem is that the mixing coefficient for the reflection and background layers depends on the angle of incidence and the orientation of the plane of incidence, which are spatially varying over the pixels of an image. Exploiting physical properties of polarization for a double-surfaced glass medium, we propose a multiscale scheme which automatically finds the optimal separation of the reflection and background layers. Through experiments, we demonstrate that our approach can generate superior results to those of previous methods.

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Publisher site [BibTex]

Publisher site [BibTex]


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Dynamic Modeling and Control of Voice-Coil Actuators for High-Fidelity Display of Haptic Vibrations

McMahan, W., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 115-122, Houston, Texas, USA, February 2014, Oral presentation given by Kuchenbecker (inproceedings)

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[BibTex]

[BibTex]


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A Wearable Device for Controlling a Robot Gripper With Fingertip Contact, Pressure, Vibrotactile, and Grip Force Feedback

Pierce, R. M., Fedalei, E. A., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 19-25, Houston, Texas, USA, February 2014, Oral presentation given by Pierce (inproceedings)

hi

[BibTex]

[BibTex]


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Methods for Robotic Tool-Mediated Haptic Surface Recognition

Romano, J. M., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 49-56, Houston, Texas, USA, February 2014, Oral presentation given by Kuchenbecker. Finalist for Best Paper Award (inproceedings)

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[BibTex]

[BibTex]


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Simpler, faster, more accurate melanocytic lesion segmentation through MEDS

Peruch, F., Bogo, F., Bonazza, M., Cappelleri, V., Peserico, E.

IEEE Transactions on Biomedical Engineering, 61(2):557-565, February 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Control of a Virtual Robot with Fingertip Contact, Pressure, Vibrotactile, and Grip Force Feedback

Pierce, R. M., Fedalei, E. A., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Houston, Texas, USA, February 2014 (misc)

hi

[BibTex]

[BibTex]


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One Hundred Data-Driven Haptic Texture Models and Open-Source Methods for Rendering on 3D Objects

Culbertson, H., Delgado, J. J. L., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 319-325, Houston, Texas, USA, February 2014, Poster presentation given by Culbertson. Finalist for Best Poster Award (inproceedings)

hi

[BibTex]

[BibTex]


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A Modular Tactile Motion Guidance System

Kuchenbecker, K. J., Anon, A. M., Barkin, T., deVillafranca, K., Lo, M.

Hands-on demonstration presented at IEEE Haptics Symposium, Houston, Texas, USA, February 2014 (misc)

hi

[BibTex]

[BibTex]


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The design of microfibers with mushroom-shaped tips for optimal adhesion

Sitti, M., Aksak, B.

February 2014, US Patent App. 14/766,561 (misc)

pi

[BibTex]

[BibTex]


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The Penn Haptic Texture Toolkit

Culbertson, H., Delgado, J. J. L., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Houston, Texas, USA, February 2014 (misc)

hi

[BibTex]

[BibTex]


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3D nanofabrication on complex seed shapes using glancing angle deposition

Hyeon-Ho, J., Mark, A. G., Gibbs, J. G., Reindl, T., Waizmann, U., Weis, J., Fischer, P.

In 2014 IEEE 27th International Conference on Micro Electro Mechanical Systems (MEMS), pages: 437-440, January 2014 (inproceedings)

Abstract
Three-dimensional (3D) fabrication techniques promise new device architectures and enable the integration of more components, but fabricating 3D nanostructures for device applications remains challenging. Recently, we have performed glancing angle deposition (GLAD) upon a nanoscale hexagonal seed array to create a variety of 3D nanoscale objects including multicomponent rods, helices, and zigzags [1]. Here, in an effort to generalize our technique, we present a step-by-step approach to grow 3D nanostructures on more complex nanoseed shapes and configurations than before. This approach allows us to create 3D nanostructures on nanoseeds regardless of seed sizes and shapes.

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DOI [BibTex]

DOI [BibTex]


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Juggling revisited — A voxel based morphometry study with expert jugglers

Gerber, P., Schlaffke, L., Heba, S., Greenlee, M., Schultz, T., Schmidt-Wilcke, T.

NeuroImage, 95, pages: 320-325, 2014 (article)

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Web DOI [BibTex]

Web DOI [BibTex]


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Assessing attention and cognitive function in completely locked-in state with event-related brain potentials and epidural electrocorticography

Bensch, M., Martens, S., Halder, S., Hill, J., Nijboer, F., Ramos, A., Birbaumer, N., Bodgan, M., Kotchoubey, B., Rosenstiel, W., Schölkopf, B., Gharabaghi, A.

Journal of Neural Engineering, 11(2):026006, 2014 (article)

Abstract
Objective. Patients in the completely locked-in state (CLIS), due to, for example, amyotrophic lateral sclerosis (ALS), no longer possess voluntary muscle control. Assessing attention and cognitive function in these patients during the course of the disease is a challenging but essential task for both nursing staff and physicians. Approach. An electrophysiological cognition test battery, including auditory and semantic stimuli, was applied in a late-stage ALS patient at four different time points during a six-month epidural electrocorticography (ECoG) recording period. Event-related cortical potentials (ERP), together with changes in the ECoG signal spectrum, were recorded via 128 channels that partially covered the left frontal, temporal and parietal cortex. Main results. Auditory but not semantic stimuli induced significant and reproducible ERP projecting to specific temporal and parietal cortical areas. N1/P2 responses could be detected throughout the whole study period. The highest P3 ERP was measured immediately after the patient's last communication through voluntary muscle control, which was paralleled by low theta and high gamma spectral power. Three months after the patient's last communication, i.e., in the CLIS, P3 responses could no longer be detected. At the same time, increased activity in low-frequency bands and a sharp drop of gamma spectral power were recorded. Significance. Cortical electrophysiological measures indicate at least partially intact attention and cognitive function during sparse volitional motor control for communication. Although the P3 ERP and frequency-specific changes in the ECoG spectrum may serve as indicators for CLIS, a close-meshed monitoring will be required to define the exact time point of the transition.

ei

DOI [BibTex]

DOI [BibTex]


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Identifiability of Gaussian Structural Equation Models with Equal Error Variances

Peters, J., Bühlman, P.

Biometrika, 101(1):219-228, 2014 (article)

ei

DOI [BibTex]


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Dynamical source analysis of hippocampal sharp-wave ripple episodes

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

Bernstein Conference, 2014 (poster)

ei

DOI [BibTex]

DOI [BibTex]


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Quantifying the effect of intertrial dependence on perceptual decisions

Fründ, I., Wichmann, F., Macke, J.

Journal of Vision, 14(7):1-16, 2014 (article)

ei

Web PDF link (url) DOI [BibTex]

Web PDF link (url) DOI [BibTex]