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2016


Skinned multi-person linear model
Skinned multi-person linear model

Black, M.J., Loper, M., Mahmood, N., Pons-Moll, G., Romero, J.

December 2016, Application PCT/EP2016/064610 (misc)

Abstract
The invention comprises a learned model of human body shape and pose dependent shape variation that is more accurate than previous models and is compatible with existing graphics pipelines. Our Skinned Multi-Person Linear model (SMPL) is a skinned vertex based model that accurately represents a wide variety of body shapes in natural human poses. The parameters of the model are learned from data including the rest pose template, blend weights, pose-dependent blend shapes, identity- dependent blend shapes, and a regressor from vertices to joint locations. Unlike previous models, the pose-dependent blend shapes are a linear function of the elements of the pose rotation matrices. This simple formulation enables training the entire model from a relatively large number of aligned 3D meshes of different people in different poses. The invention quantitatively evaluates variants of SMPL using linear or dual- quaternion blend skinning and show that both are more accurate than a Blend SCAPE model trained on the same data. In a further embodiment, the invention realistically models dynamic soft-tissue deformations. Because it is based on blend skinning, SMPL is compatible with existing rendering engines and we make it available for research purposes.

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Google Patents [BibTex]

2016


Google Patents [BibTex]


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Numerical Investigation of Frictional Forces Between a Finger and a Textured Surface During Active Touch

Khojasteh, B., Janko, M., Visell, Y.

Extended abstract presented in form of an oral presentation at the 3rd International Conference on BioTribology (ICoBT), London, England, September 2016 (misc)

Abstract
The biomechanics of the human finger pad has been investigated in relation to motor behaviour and sensory function in the upper limb. While the frictional properties of the finger pad are important for grip and grasp function, recent attention has also been given to the roles played by friction when perceiving a surface via sliding contact. Indeed, the mechanics of sliding contact greatly affect stimuli felt by the finger scanning a surface. Past research has shed light on neural mechanisms of haptic texture perception, but the relation with time-resolved frictional contact interactions is unknown. Current biotribological models cannot predict time-resolved frictional forces felt by a finger as it slides on a rough surface. This constitutes a missing link in understanding the mechanical basis of texture perception. To ameliorate this, we developed a two-dimensional finite element numerical simulation of a human finger pad in sliding contact with a textured surface. Our model captures bulk mechanical properties, including hyperelasticity, dissipation, and tissue heterogeneity, and contact dynamics. To validate it, we utilized a database of measurements that we previously captured with a variety of human fingers and surfaces. By designing the simulations to match the measurements, we evaluated the ability of the FEM model to predict time-resolved sliding frictional forces. We varied surface texture wavelength, sliding speed, and normal forces in the experiments. An analysis of the results indicated that both time- and frequency-domain features of forces produced during finger-surface sliding interactions were reproduced, including many of the phenomena that we observed in analyses of real measurements, including quasiperiodicity, harmonic distortion and spectral decay in the frequency domain, and their dependence on kinetics and surface properties. The results shed light on frictional signatures of surface texture during active touch, and may inform understanding of the role played by friction in texture discrimination.

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[BibTex]

[BibTex]


Behavioral Learning and Imitation for Music-Based Robotic Therapy for Children with Autism Spectrum Disorder
Behavioral Learning and Imitation for Music-Based Robotic Therapy for Children with Autism Spectrum Disorder

Burns, R., Nizambad, S., Park, C. H., Jeon, M., Howard, A.

Workshop paper (5 pages) at the RO-MAN Workshop on Behavior Adaptation, Interaction and Learning for Assistive Robotics, August 2016 (misc)

Abstract
In this full workshop paper, we discuss the positive impacts of robot, music, and imitation therapies on children with autism. We also discuss the use of Laban Motion Analysis (LMA) to identify emotion through movement and posture cues. We present our preliminary studies of the "Five Senses" game that our two robots, Romo the penguin and Darwin Mini, partake in. Using an LMA-focused approach (enabled by our skeletal tracking Kinect algorithm), we find that our participants show increased frequency of movement and speed when the game has a musical accompaniment. Therefore, participants may have increased engagement with our robots and game if music is present. We also begin exploring motion learning for future works.

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link (url) [BibTex]

link (url) [BibTex]


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Design and evaluation of a novel mechanical device to improve hemiparetic gait: a case report

Fjeld, K., Hu, S., Kuchenbecker, K. J., Vasudevan, E. V.

Extended abstract presented at the Biomechanics and Neural Control of Movement Conference (BANCOM), 2016, Poster presentation given by Fjeld (misc)

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Project Page [BibTex]

Project Page [BibTex]


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One Sensor, Three Displays: A Comparison of Tactile Rendering from a BioTac Sensor

Brown, J. D., Ibrahim, M., Chase, E. D. Z., Pacchierotti, C., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Philadelphia, Pennsylvania, USA, April 2016 (misc)

hi

[BibTex]

[BibTex]


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Special Issue on Causal Discovery and Inference

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

ACM Transactions on Intelligent Systems and Technology (TIST), 7(2), January 2016, (Guest Editors) (misc)

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[BibTex]

[BibTex]


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Empirical Inference (2010-2015)
Scientific Advisory Board Report, 2016 (misc)

ei

pdf [BibTex]

pdf [BibTex]


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Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set

Mittal, A., Raj, A., Namboodiri, V. P., Tuytelaars, T.

2016 (misc)

ei

Arxiv [BibTex]

Arxiv [BibTex]


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Designing Human-Robot Exercise Games for Baxter

Fitter, N. T., Hawkes, D. T., Johnson, M. J., Kuchenbecker, K. J.

2016, Late-breaking results report presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (misc)

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Project Page [BibTex]

Project Page [BibTex]


Perceiving Systems (2011-2015)
Perceiving Systems (2011-2015)
Scientific Advisory Board Report, 2016 (misc)

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pdf [BibTex]

pdf [BibTex]


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Interface-controlled phenomena in nanomaterials

Mittemeijer, Eric J.; Wang, Zumin

2016 (mpi_year_book)

Abstract
Nanosized material systems characteristically exhibit an excessively high internal interface density. A series of previously unknown phenomena in nanomaterials have been disclosed that are fundamentally caused by the presence of interfaces. Thus anomalously large and small lattice parameters in nanocrystalline metals, quantum stress oscillations in growing nanofilms, and extraordinary atomic mobility at ultralow temperatures have been observed and explained. The attained understanding for these new phenomena can lead to new, sophisticated applications of nanomaterials in advanced technologies.

link (url) [BibTex]

link (url) [BibTex]


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Robots learn how to see

Geiger, A.

2016 (mpi_year_book)

Abstract
Autonomous vehicles and intelligent service robots could soon contribute to making our lives more pleasant and secure. However, for autonomous operation such systems first need to learn the perception process itself. This involves measuring distances and motions, detecting objects and interpreting the threedimensional world as a whole. While humans perceive their environment with seemingly little efforts, computers first need to be trained for these tasks. Our research is concerned with developing mathematical models which allow computers to robustly perceive their environment.

link (url) DOI [BibTex]


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Extrapolation and learning equations

Martius, G., Lampert, C. H.

2016, arXiv preprint \url{https://arxiv.org/abs/1610.02995} (misc)

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Project Page [BibTex]

Project Page [BibTex]


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IMU-Mediated Real-Time Human-Baxter Hand-Clapping Interaction

Fitter, N. T., Huang, Y. E., Mayer, J. P., Kuchenbecker, K. J.

2016, Late-breaking results report presented at the {\em IEEE/RSJ International Conference on Intelligent Robots and Systems} (misc)

hi

[BibTex]

[BibTex]

2008


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CogRob 2008: The 6th International Cognitive Robotics Workshop

Lespérance, Y., Lakemeyer, G., Peters, J., Pirri, F.

Proceedings of the 6th International Cognitive Robotics Workshop (CogRob 2008), pages: 35, Patras University Press, Patras, Greece, 6th International Cognitive Robotics Workshop (CogRob), July 2008 (proceedings)

ei

Web [BibTex]

2008


Web [BibTex]


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The Touch Thimble

Kuchenbecker, K. J., Ferguson, D., Kutzer, M., Moses, M., Okamura, A. M.

Hands-on demonstration presented at IEEE Haptics Symposium, Reno, Nevada, USA, March 2008 (misc)

hi

[BibTex]

[BibTex]

2004


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Advanced Lectures on Machine Learning

Bousquet, O., von Luxburg, U., Rätsch, G.

ML Summer Schools 2003, LNAI 3176, pages: 240, Springer, Berlin, Germany, ML Summer Schools, September 2004 (proceedings)

Abstract
Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in T{\"u}bingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references. Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.

ei

Web [BibTex]

2004


Web [BibTex]


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Pattern Recognition: 26th DAGM Symposium, LNCS, Vol. 3175

Rasmussen, C., Bülthoff, H., Giese, M., Schölkopf, B.

Proceedings of the 26th Pattern Recognition Symposium (DAGM‘04), pages: 581, Springer, Berlin, Germany, 26th Pattern Recognition Symposium, August 2004 (proceedings)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference

Thrun, S., Saul, L., Schölkopf, B.

Proceedings of the Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), pages: 1621, MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (proceedings)

Abstract
The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees—physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.

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Web [BibTex]

Web [BibTex]


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Statistische Lerntheorie und Empirische Inferenz

Schölkopf, B.

Jahrbuch der Max-Planck-Gesellschaft, 2004, pages: 377-382, 2004 (misc)

Abstract
Statistical learning theory studies the process of inferring regularities from empirical data. The fundamental problem is what is called generalization: how it is possible to infer a law which will be valid for an infinite number of future observations, given only a finite amount of data? This problem hinges upon fundamental issues of statistics and science in general, such as the problems of complexity of explanations, a priori knowledge, and representation of data.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Nanoscale Materials for Energy Storage
{Materials Science \& Engineering B}, 108, pages: 292, Elsevier, 2004 (misc)

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[BibTex]

[BibTex]