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2017


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Rubbing Against Blood Clots Using Helical Robots: Modeling and In Vitro Experimental Validation

Khalil, I. S., Tabak, A. F., Sadek, K., Mahdy, D., Hamdi, N., Sitti, M.

IEEE Robotics and Automation Letters, 2(2):927-934, IEEE, January 2017 (article)

Abstract
The risk of side effects from thrombolytic agents can be minimized by using smaller doses, assisted by mechanical rubbing against blood clots using helical robots. Quantifying this observation, we study the influence of rubbing against clots on their removal rate in vitro. First, we present a hydrodynamic model of the helical robot based on the resistive-force theory to investigate the rubbing behavior of the clots using robot driven by two rotating dipole fields. Second, we experimentally evaluate the influence of the rubbing on the removal rate of the blood clots. Not only do we find that the removal rate of mechanical rubbing (-0.56 ± 0.27 mm3 /min) is approximately three times greater than the dissolution rate of chemical lysis using streptokinase (-0.17 ± 0.032 mm3/min), but we also show that this removal rate can be controlled via the rubbing speed of the robot.

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DOI [BibTex]

2017


DOI [BibTex]


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Nanoscale topographical control of capillary assembly of nanoparticles

Flauraud, V., Mastrangeli, M., Bernasconi, G., Butet, J., Alexander, D., Shahrabi, E., Martin, O., Brugger, J.

Scientific Reports, Nature Nanotechnology, 12, pages: 73-80, January 2017 (article)

Abstract
Predetermined and selective placement of nanoparticles onto large-area substrates with nanometre-scale precision is essential to harness the unique properties of nanoparticle assemblies, in particular for functional optical and electro-optical nanodevices. Unfortunately, such high spatial organization is currently beyond the reach of top-down nanofabrication techniques alone. Here, we demonstrate that topographic features comprising lithographed funnelled traps and auxiliary sidewalls on a solid substrate can deterministically direct the capillary assembly of Au nanorods to attain simultaneous control of position, orientation and interparticle distance at the nanometre level. We report up to 100% assembly yield over centimetre-scale substrates. We achieve this by optimizing the three sequential stages of capillary nanoparticle assembly: insertion of nanorods into the traps, resilience against the receding suspension front and drying of the residual solvent. Finally, using electron energy-loss spectroscopy we characterize the spectral response and near-field properties of spatially programmable Au nanorod dimers, highlighting the opportunities for precise tunability of the plasmonic modes in larger assemblies.

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DOI [BibTex]

DOI [BibTex]


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Importance of Matching Physical Friction, Hardness, and Texture in Creating Realistic Haptic Virtual Surfaces

Culbertson, H., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 10(1):63-74, January 2017 (article)

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[BibTex]


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Effects of Grip-Force, Contact, and Acceleration Feedback on a Teleoperated Pick-and-Place Task

Khurshid, R. P., Fitter, N. T., Fedalei, E. A., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 10(1):40-53, January 2017 (article)

hi

[BibTex]

[BibTex]


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Multiaxial Polarity Determines Individual Cellular and Nuclear Chirality

Raymond, M. J., Ray, P., Kaur, G., Fredericks, M., Singh, A. V., Wan, L. Q.

Cellular and Molecular Bioengineering, 10(1):63-74, 2017 (article)

Abstract
Intrinsic cell chirality has been implicated in the left--right (LR) asymmetry of embryonic development. Impaired cell chirality could lead to severe birth defects in laterality. Previously, we detected cell chirality with an in vitro micropatterning system. Here, we demonstrate for the first time that chirality can be quantified as the coordination of multiaxial polarization of individual cells and nuclei. Using an object labeling, connected component based method, we characterized cell chirality based on cell and nuclear shape polarization and nuclear positioning of each cell in multicellular patterns of epithelial cells. We found that the cells adopted a LR bias the boundaries by positioning the sharp end towards the leading edge and leaving the nucleus at the rear. This behavior is consistent with the directional migration observed previously on the boundary of micropatterns. Although the nucleus is chirally aligned, it is not strongly biased towards or away from the boundary. As the result of the rear positioning of nuclei, the nuclear positioning has an opposite chirality to that of cell alignment. Overall, our results have revealed deep insights of chiral morphogenesis as the coordination of multiaxial polarization at the cellular and subcellular levels.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills

Kupcsik, A., Deisenroth, M., Peters, J., Ai Poh, L., Vadakkepat, V., Neumann, G.

Artificial Intelligence, 247, pages: 415-439, 2017, Special Issue on AI and Robotics (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Anticipatory Action Selection for Human-Robot Table Tennis

Wang, Z., Boularias, A., Mülling, K., Schölkopf, B., Peters, J.

Artificial Intelligence, 247, pages: 399-414, 2017, Special Issue on AI and Robotics (article)

Abstract
Abstract Anticipation can enhance the capability of a robot in its interaction with humans, where the robot predicts the humans' intention for selecting its own action. We present a novel framework of anticipatory action selection for human-robot interaction, which is capable to handle nonlinear and stochastic human behaviors such as table tennis strokes and allows the robot to choose the optimal action based on prediction of the human partner's intention with uncertainty. The presented framework is generic and can be used in many human-robot interaction scenarios, for example, in navigation and human-robot co-manipulation. In this article, we conduct a case study on human-robot table tennis. Due to the limited amount of time for executing hitting movements, a robot usually needs to initiate its hitting movement before the opponent hits the ball, which requires the robot to be anticipatory based on visual observation of the opponent's movement. Previous work on Intention-Driven Dynamics Models (IDDM) allowed the robot to predict the intended target of the opponent. In this article, we address the problem of action selection and optimal timing for initiating a chosen action by formulating the anticipatory action selection as a Partially Observable Markov Decision Process (POMDP), where the transition and observation are modeled by the \{IDDM\} framework. We present two approaches to anticipatory action selection based on the \{POMDP\} formulation, i.e., a model-free policy learning method based on Least-Squares Policy Iteration (LSPI) that employs the \{IDDM\} for belief updates, and a model-based Monte-Carlo Planning (MCP) method, which benefits from the transition and observation model by the IDDM. Experimental results using real data in a simulated environment show the importance of anticipatory action selection, and that \{POMDPs\} are suitable to formulate the anticipatory action selection problem by taking into account the uncertainties in prediction. We also show that existing algorithms for POMDPs, such as \{LSPI\} and MCP, can be applied to substantially improve the robot's performance in its interaction with humans.

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DOI [BibTex]

DOI [BibTex]


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easyGWAS: A Cloud-based Platform for Comparing the Results of Genome-wide Association Studies

Grimm, D., Roqueiro, D., Salome, P., Kleeberger, S., Greshake, B., Zhu, W., Liu, C., Lippert, C., Stegle, O., Schölkopf, B., Weigel, D., Borgwardt, K.

The Plant Cell, 29(1):5-19, 2017 (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation

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

Molecular Imaging and Biology, 19(3):391-397, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Early Stopping Without a Validation Set

Mahsereci, M., Balles, L., Lassner, C., Hennig, P.

arXiv preprint arXiv:1703.09580, 2017 (article)

Abstract
Early stopping is a widely used technique to prevent poor generalization performance when training an over-expressive model by means of gradient-based optimization. To find a good point to halt the optimizer, a common practice is to split the dataset into a training and a smaller validation set to obtain an ongoing estimate of the generalization performance. In this paper we propose a novel early stopping criterion which is based on fast-to-compute, local statistics of the computed gradients and entirely removes the need for a held-out validation set. Our experiments show that this is a viable approach in the setting of least-squares and logistic regression as well as neural networks.

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link (url) Project Page [BibTex]


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Pre-Movement Contralateral EEG Low Beta Power Is Modulated with Motor Adaptation Learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages: 934-938, 2017 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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Elements of Causal Inference - Foundations and Learning Algorithms

Peters, J., Janzing, D., Schölkopf, B.

Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

ei

PDF [BibTex]

PDF [BibTex]


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Krylov Subspace Recycling for Fast Iterative Least-Squares in Machine Learning

Roos, F. D., Hennig, P.

arXiv preprint arXiv:1706.00241, 2017 (article)

Abstract
Solving symmetric positive definite linear problems is a fundamental computational task in machine learning. The exact solution, famously, is cubicly expensive in the size of the matrix. To alleviate this problem, several linear-time approximations, such as spectral and inducing-point methods, have been suggested and are now in wide use. These are low-rank approximations that choose the low-rank space a priori and do not refine it over time. While this allows linear cost in the data-set size, it also causes a finite, uncorrected approximation error. Authors from numerical linear algebra have explored ways to iteratively refine such low-rank approximations, at a cost of a small number of matrix-vector multiplications. This idea is particularly interesting in the many situations in machine learning where one has to solve a sequence of related symmetric positive definite linear problems. From the machine learning perspective, such deflation methods can be interpreted as transfer learning of a low-rank approximation across a time-series of numerical tasks. We study the use of such methods for our field. Our empirical results show that, on regression and classification problems of intermediate size, this approach can interpolate between low computational cost and numerical precision.

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link (url) [BibTex]


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Minimax Estimation of Kernel Mean Embeddings

Tolstikhin, I., Sriperumbudur, B., Muandet, K.

Journal of Machine Learning Research, 18(86):1-47, 2017 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


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Kernel Mean Embedding of Distributions: A Review and Beyond

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

Foundations and Trends in Machine Learning, 10(1-2):1-141, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Case Series: Slowing Alpha Rhythm in Late-Stage ALS Patients

Hohmann, M. R., Fomina, T., Jayaram, V., Emde, T., Just, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

Clinical Neurophysiology, 129(2):406-408, 2017 (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Appealing Avatars from 3D Body Scans: Perceptual Effects of Stylization

Fleming, R., Mohler, B. J., Romero, J., Black, M. J., Breidt, M.

In Computer Vision, Imaging and Computer Graphics Theory and Applications: 11th International Joint Conference, VISIGRAPP 2016, Rome, Italy, February 27 – 29, 2016, Revised Selected Papers, pages: 175-196, Springer International Publishing, 2017 (inbook)

Abstract
Using styles derived from existing popular character designs, we present a novel automatic stylization technique for body shape and colour information based on a statistical 3D model of human bodies. We investigate whether such stylized body shapes result in increased perceived appeal with two different experiments: One focuses on body shape alone, the other investigates the additional role of surface colour and lighting. Our results consistently show that the most appealing avatar is a partially stylized one. Importantly, avatars with high stylization or no stylization at all were rated to have the least appeal. The inclusion of colour information and improvements to render quality had no significant effect on the overall perceived appeal of the avatars, and we observe that the body shape primarily drives the change in appeal ratings. For body scans with colour information, we found that a partially stylized avatar was perceived as most appealing.

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publisher site pdf DOI [BibTex]

publisher site pdf DOI [BibTex]


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Computing with Uncertainty

Hennig, P.

2017 (mpi_year_book)

Abstract
Machine learning requires computer hardware to reliable and efficiently compute estimations for ever more complex and fundamentally incomputable quantities. A research team at MPI for Intelligent Systems in Tübingen develops new algorithms which purposely lower the precision of computations and return an explicit measure of uncertainty over the correct result alongside the estimate. Doing so allows for more flexible management of resources, and increases the reliability of intelligent systems.

link (url) DOI [BibTex]


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Change-point Detection and Kernels Methods

Garreau, D.

Ecole Normale Supérieure / PSL Research University, 2017 (thesis)

link (url) [BibTex]

link (url) [BibTex]


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Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings

Kanagawa, M., Sriperumbudur, B. K., Fukumizu, K.

Arxiv e-prints, arXiv:1709.00147v1 [math.NA], 2017 (article)

Abstract
This paper presents convergence analysis of kernel-based quadrature rules in misspecified settings, focusing on deterministic quadrature in Sobolev spaces. In particular, we deal with misspecified settings where a test integrand is less smooth than a Sobolev RKHS based on which a quadrature rule is constructed. We provide convergence guarantees based on two different assumptions on a quadrature rule: one on quadrature weights, and the other on design points. More precisely, we show that convergence rates can be derived (i) if the sum of absolute weights remains constant (or does not increase quickly), or (ii) if the minimum distance between distance design points does not decrease very quickly. As a consequence of the latter result, we derive a rate of convergence for Bayesian quadrature in misspecified settings. We reveal a condition on design points to make Bayesian quadrature robust to misspecification, and show that, under this condition, it may adaptively achieve the optimal rate of convergence in the Sobolev space of a lesser order (i.e., of the unknown smoothness of a test integrand), under a slightly stronger regularity condition on the integrand.

pn

arXiv [BibTex]

arXiv [BibTex]


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Distilling Information Reliability and Source Trustworthiness from Digital Traces

Tabibian, B., Valera, I., Farajtabar, M., Song, L., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the 26th International Conference on World Wide Web (WWW), pages: 847-855, (Editors: Barrett, R., Cummings, R., Agichtein, E. and Gabrilovich, E. ), ACM, 2017 (conference)

ei

Project DOI [BibTex]

Project DOI [BibTex]


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Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach

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

Journal of Nuclear Medicine, 58(4):651-657, 2017 (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Weakly-Supervised Localization of Diabetic Retinopathy Lesions in Retinal Fundus Images

Gondal, M. W., Köhler, J. M., Grzeszick, R., Fink, G., Hirsch, M.

IEEE International Conference on Image Processing (ICIP), pages: 2069-2073, 2017 (conference)

ei

arXiv DOI [BibTex]

arXiv DOI [BibTex]


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Electroencephalographic identifiers of motor adaptation learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Journal of Neural Engineering, 14(4):046027, 2017 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


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Gene delivery particle engineering strategies for shape-dependent targeting of cells and tissues.

Kozielski, K., Sitti, M.

Current gene therapy, 17, 2017 (article)

Abstract
Background: Successful gene delivery requires overcoming both systemic and intracellular obstacles before the nucleic acid cargo can successfully reach its tissue and subcellular target location. Materials & Methods: Non-viral mechanisms to enable targeting while avoiding off-target delivery have arisen via biological, chemical, and physical engineering strategies. Discussion: Herein we will discuss the physical parameters in particle design that promote tissue- and cell-targeted delivery of genetic cargo. We will discuss systemic concerns, such as circulation, tissue localization, and clearance, as well as cell-scale obstacles, such as cellular uptake and nucleic acid packaging. Conclusion: In particular, we will focus on engineering particle shape and size in order to enhance delivery and promote precise targeting. We will also address methods to program or change particle shape in situ using environmentally triggered cues.

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DOI [BibTex]


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Self-Organized Behavior Generation for Musculoskeletal Robots

Der, R., Martius, G.

Frontiers in Neurorobotics, 11, pages: 8, 2017 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination

Zhang, K., Huang, B., Zhang, J., Glymour, C., Schölkopf, B.

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI), pages: 1347-1353, (Editors: Carles Sierra), 2017 (conference)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Detecting distortions of peripherally presented letter stimuli under crowded conditions

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

Attention, Perception, & Psychophysics, 79(3):850-862, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Personalized Brain-Computer Interface Models for Motor Rehabilitation

Mastakouri, A., Weichwald, S., Ozdenizci, O., Meyer, T., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages: 3024-3029, 2017 (conference)

ei

ArXiv PDF DOI [BibTex]

ArXiv PDF DOI [BibTex]


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Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows

Huang, B., Zhang, K., Zhang, J., Sanchez-Romero, R., Glymour, C., Schölkopf, B.

IEEE 17th International Conference on Data Mining (ICDM), pages: 913-918, (Editors: Vijay Raghavan,Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu), 2017 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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Multi-fractal characterization of bacterial swimming dynamics: a case study on real and simulated Serratia marcescens

Koorehdavoudi, H., Bogdan, P., Wei, G., Marculescu, R., Zhuang, J., Carlsen, R. W., Sitti, M.

Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 473(2203), The Royal Society, 2017 (article)

Abstract
To add to the current state of knowledge about bacterial swimming dynamics, in this paper, we study the fractal swimming dynamics of populations of Serratia marcescens bacteria both in vitro and in silico, while accounting for realistic conditions like volume exclusion, chemical interactions, obstacles and distribution of chemoattractant in the environment. While previous research has shown that bacterial motion is non-ergodic, we demonstrate that, besides the non-ergodicity, the bacterial swimming dynamics is multi-fractal in nature. Finally, we demonstrate that the multi-fractal characteristic of bacterial dynamics is strongly affected by bacterial density and chemoattractant concentration.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Automatic detection of motion artifacts in MR images using CNNS

Meding, K., Loktyushin, A., Hirsch, M.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), pages: 811-815, 2017 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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Learning to Filter Object Detections

Prokudin, S., Kappler, D., Nowozin, S., Gehler, P.

In Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland, September 12–15, 2017, Proceedings, pages: 52-62, Springer International Publishing, Cham, 2017 (inbook)

Abstract
Most object detection systems consist of three stages. First, a set of individual hypotheses for object locations is generated using a proposal generating algorithm. Second, a classifier scores every generated hypothesis independently to obtain a multi-class prediction. Finally, all scored hypotheses are filtered via a non-differentiable and decoupled non-maximum suppression (NMS) post-processing step. In this paper, we propose a filtering network (FNet), a method which replaces NMS with a differentiable neural network that allows joint reasoning and re-scoring of the generated set of hypotheses per image. This formulation enables end-to-end training of the full object detection pipeline. First, we demonstrate that FNet, a feed-forward network architecture, is able to mimic NMS decisions, despite the sequential nature of NMS. We further analyze NMS failures and propose a loss formulation that is better aligned with the mean average precision (mAP) evaluation metric. We evaluate FNet on several standard detection datasets. Results surpass standard NMS on highly occluded settings of a synthetic overlapping MNIST dataset and show competitive behavior on PascalVOC2007 and KITTI detection benchmarks.

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Paper link (url) DOI [BibTex]

Paper link (url) DOI [BibTex]


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Microemulsion-Based Soft Bacteria-Driven Microswimmers for Active Cargo Delivery

Singh, A. V., Hosseinidoust, Z., Park, B., Yasa, O., Sitti, M.

ACS Nano, 0(0):null, 2017, PMID: 28858477 (article)

Abstract
Biohybrid cell-driven microsystems offer unparalleled possibilities for realization of soft microrobots at the micron scale. Here, we introduce a bacteria-driven microswimmer that combines the active locomotion and sensing capabilities of bacteria with the desirable encapsulation and viscoelastic properties of a soft double-micelle microemulsion for active transport and delivery of cargo (e.g., imaging agents, genes, and drugs) to living cells. Quasi-monodisperse double emulsions were synthesized with an aqueous core that encapsulated the fluorescence imaging agents, as a proof-of-concept cargo in this study, and an outer oil shell that was functionalized with streptavidin for specific and stable attachment of biotin-conjugated Escherichia coli. Motile bacteria effectively propelled the soft microswimmers across a Transwell membrane, actively delivering imaging agents (i.e., dyes) encapsulated inside of the micelles to a monolayer of cultured MCF7 breast cancer and J744A.1 macrophage cells, which enabled real-time, live-cell imaging of cell organelles, namely mitochondria, endoplasmic reticulum, and Golgi body. This in vitro model demonstrates the proof-of-concept feasibility of the proposed soft microswimmers and offers promise for potential biomedical applications in active and/or targeted transport and delivery of imaging agents, drugs, stem cells, siRNA, and therapeutic genes to live tissue in in vitro disease models (e.g., organ-on-a-chip devices) and stagnant or low-flow-velocity fluidic regions of the human body.

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


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Biomechanics and Locomotion Control in Legged Animals and Legged Robots

Sproewitz, A., Heim, S.

2017 (mpi_year_book)

Abstract
An animal's running gait is dynamic, efficient, elegant, and adaptive. We see locomotion in animals as an orchestrated interplay of the locomotion apparatus, interacting with its environment. The Dynamic Locomotion Group at the Max Planck Institute for Intelligent Systems in Stuttgart develops novel legged robots to decipher aspects of biomechanics and neuromuscular control of legged locomotion in animals, and to understand general principles of locomotion.

link (url) DOI [BibTex]


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Linking Mechanics and Learning

Heim, S., Grimminger, F., Özge, D., Spröwitz, A.

In Proceedings of Dynamic Walking 2017, 2017 (inproceedings)

dlg

[BibTex]

[BibTex]


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Discriminative k-shot learning using probabilistic models

Bauer*, M., Rojas-Carulla*, M., Świątkowski, J. B., Schölkopf, B., Turner, R. E.

Second Workshop on Bayesian Deep Learning at the 31st Conference on Neural Information Processing Systems (NIPS) , 2017, *equal contribution (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Mode Evolution in Strongly Coupled Plasmonic Dolmens Fabricated by Templated Assembly

Flauraud, V., Bernasconi, G. D., Butet, J., Mastrangeli, M., Alexander, D. T. L., Martin, O. J. F., Brugger, J.

ACS Photonics, 4(7):1661-1668, 2017 (article)

Abstract
Plasmonic antennas have enabled a wealth of applications that exploit tailored near-fields and radiative properties, further endowed by the bespoke interactions of multiple resonant building blocks. Specifically, when the interparticle distances are reduced to a few nanometers, coupling may be greatly enhanced leading to ultimate near-field intensities and confinement along with a large energy splitting of resonant modes. While this concept is well-known, the fabrication and characterization of suitable multimers with controlled geometries and few-nanometer gaps remains highly challenging. In this article, we present the topographically templated assembly of single-crystal colloidal gold nanorods into trimers, with a dolmen geometry. This fabrication method enables the precise positioning of high-quality nanorods, with gaps as small as 1.5 nm, which permits a gradual and controlled symmetry breaking by tuning the arrangement of these strongly coupled nanostructures. To characterize the fabricated structures, we perform electron energy loss spectroscopy (EELS) near-field hyperspectral imaging and geometrically accurate EELS, plane wave, and eigenmode full-wave computations to reveal the principles governing the electromagnetic response of such nanostructures that have been extensively studied under plane wave excitation for their Fano resonant properties. These experiments track the evolution of the multipolar interactions with high accuracy as the antenna geometry varies. Our results provide new insights in strongly coupled single-crystal building blocks and open news opportunities for the design and fabrication of plasmonic systems.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Unsupervised clustering of EOG as a viable substitute for optical eye-tracking

Flad, N., Fomina, T., Bülthoff, H. H., Chuang, L. L.

In First Workshop on Eye Tracking and Visualization (ETVIS 2015), pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

ei

DOI [BibTex]

DOI [BibTex]


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BundleMAP: Anatomically Localized Classification, Regression, and Hypothesis Testing in Diffusion MRI

Khatami, M., Schmidt-Wilcke, T., Sundgren, P. C., Abbasloo, A., Schölkopf, B., Schultz, T.

Pattern Recognition, 63, pages: 593-600, 2017 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Data-Driven Physics for Human Soft Tissue Animation

Kim, M., Pons-Moll, G., Pujades, S., Bang, S., Kim, J., Black, M., Lee, S.

ACM Transactions on Graphics, (Proc. SIGGRAPH), 36(4), 2017 (article)

Abstract
Data driven models of human poses and soft-tissue deformations can produce very realistic results, but they only model the visible surface of the human body and cannot create skin deformation due to interactions with the environment. Physical simulations can generalize to external forces, but their parameters are difficult to control. In this paper, we present a layered volumetric human body model learned from data. Our model is composed of a data-driven inner layer and a physics-based external layer. The inner layer is driven with a volumetric statistical body model (VSMPL). The soft tissue layer consists of a tetrahedral mesh that is driven using the finite element method (FEM). Model parameters, namely the segmentation of the body into layers and the soft tissue elasticity, are learned directly from 4D registrations of humans exhibiting soft tissue deformations. The learned two layer model is a realistic full-body avatar that generalizes to novel motions and external forces. Experiments show that the resulting avatars produce realistic results on held out sequences and react to external forces. Moreover, the model supports the retargeting of physical properties from one avatar when they share the same topology.

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video paper link (url) [BibTex]

video paper link (url) [BibTex]


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Local Group Invariant Representations via Orbit Embeddings

Raj, A., Kumar, A., Mroueh, Y., Fletcher, T., Schölkopf, B.

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017), 54, pages: 1225-1235, Proceedings of Machine Learning Research, (Editors: Aarti Singh and Jerry Zhu), 2017 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Learning Inference Models for Computer Vision

Jampani, V.

MPI for Intelligent Systems and University of Tübingen, 2017 (phdthesis)

Abstract
Computer vision can be understood as the ability to perform 'inference' on image data. Breakthroughs in computer vision technology are often marked by advances in inference techniques, as even the model design is often dictated by the complexity of inference in them. This thesis proposes learning based inference schemes and demonstrates applications in computer vision. We propose techniques for inference in both generative and discriminative computer vision models. Despite their intuitive appeal, the use of generative models in vision is hampered by the difficulty of posterior inference, which is often too complex or too slow to be practical. We propose techniques for improving inference in two widely used techniques: Markov Chain Monte Carlo (MCMC) sampling and message-passing inference. Our inference strategy is to learn separate discriminative models that assist Bayesian inference in a generative model. Experiments on a range of generative vision models show that the proposed techniques accelerate the inference process and/or converge to better solutions. A main complication in the design of discriminative models is the inclusion of prior knowledge in a principled way. For better inference in discriminative models, we propose techniques that modify the original model itself, as inference is simple evaluation of the model. We concentrate on convolutional neural network (CNN) models and propose a generalization of standard spatial convolutions, which are the basic building blocks of CNN architectures, to bilateral convolutions. First, we generalize the existing use of bilateral filters and then propose new neural network architectures with learnable bilateral filters, which we call `Bilateral Neural Networks'. We show how the bilateral filtering modules can be used for modifying existing CNN architectures for better image segmentation and propose a neural network approach for temporal information propagation in videos. Experiments demonstrate the potential of the proposed bilateral networks on a wide range of vision tasks and datasets. In summary, we propose learning based techniques for better inference in several computer vision models ranging from inverse graphics to freely parameterized neural networks. In generative vision models, our inference techniques alleviate some of the crucial hurdles in Bayesian posterior inference, paving new ways for the use of model based machine learning in vision. In discriminative CNN models, the proposed filter generalizations aid in the design of new neural network architectures that can handle sparse high-dimensional data as well as provide a way for incorporating prior knowledge into CNNs.

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pdf [BibTex]

pdf [BibTex]


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Recent Advances in Skin Penetration Enhancers for Transdermal Gene and Drug Delivery

Amjadia, M., Mostaghacia, B., Sittia, M.

Current Gene Therapy, 17, pages: 000-000, 2017 (article)

Abstract
There is a growing interest in transdermal delivery systems because of their noninvasive, targeted, and on-demand delivery of gene and drugs. However, efficient penetration of therapeutic compounds into the skin is still challenging largely due to the impermeability of the outermost layer of the skin, known as stratum corneum. Recently, there have been major research activities to enhance the skin penetration depth of pharmacological agents. This article reviews recent advances in the development of various strategies for skin penetration enhancement. We show that approaches such as ultrasound waves, laser, and microneedle patches have successfully been employed to physically disrupt the stratum corneum structure for enhanced transdermal delivery. Rather than physical approaches, several non-physical route have also been utilized for efficient transdermal delivery across the skin barrier. Finally, we discuss some clinical applications of transdermal delivery systems for gene and drug delivery. This paper shows that transdermal delivery devices can potentially function for diverse healthcare and medical applications while further investigations are still necessary for more efficient skin penetration of gene and drugs.

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DOI Project Page [BibTex]


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A fully dense and globally consistent 3D map reconstruction approach for GI tract to enhance therapeutic relevance of the endoscopic capsule robot

Turan, M., Pilavci, Y. Y., Jamiruddin, R., Araujo, H., Konukoglu, E., Sitti, M.

arXiv preprint arXiv:1705.06524, 2017 (article)

Abstract
In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Since the development of this technology, medical device companies and many research groups have made substantial progress in converting passive capsule endoscopes to robotic active capsule endoscopes with most of the functionality of current active flexible endoscopes. However, robotic capsule endoscopy still has some challenges. In particular, the use of such devices to generate a precise three-dimensional (3D) mapping of the entire inner organ remains an unsolved problem. Such global 3D maps of inner organs would help doctors to detect the location and size of diseased areas more accurately and intuitively, thus permitting more reliable diagnoses. To our knowledge, this paper presents the first complete pipeline for a complete 3D visual map reconstruction of the stomach. The proposed pipeline is modular and includes a preprocessing module, an image registration module, and a final shape-from-shading-based 3D reconstruction module; the 3D map is primarily generated by a combination of image stitching and shape-from-shading techniques, and is updated in a frame-by-frame iterative fashion via capsule motion inside the stomach. A comprehensive quantitative analysis of the proposed 3D reconstruction method is performed using an esophagus gastro duodenoscopy simulator, three different endoscopic cameras, and a 3D optical scanner.

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link (url) Project Page [BibTex]


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Mobile Microrobotics

Sitti, M.

Mobile Microrobotics, pages: 304, The MIT Press, Cambridge, MA, 2017 (book)

Abstract
Progress in micro- and nano-scale science and technology has created a demand for new microsystems for high-impact applications in healthcare, biotechnology, manufacturing, and mobile sensor networks. The new robotics field of microrobotics has emerged to extend our interactions and explorations to sub-millimeter scales. This is the first textbook on micron-scale mobile robotics, introducing the fundamentals of design, analysis, fabrication, and control, and drawing on case studies of existing approaches. The book covers the scaling laws that can be used to determine the dominant forces and effects at the micron scale; models forces acting on microrobots, including surface forces, friction, and viscous drag; and describes such possible microfabrication techniques as photo-lithography, bulk micromachining, and deep reactive ion etching. It presents on-board and remote sensing methods, noting that remote sensors are currently more feasible; studies possible on-board microactuators; discusses self-propulsion methods that use self-generated local gradients and fields or biological cells in liquid environments; and describes remote microrobot actuation methods for use in limited spaces such as inside the human body. It covers possible on-board powering methods, indispensable in future medical and other applications; locomotion methods for robots on surfaces, in liquids, in air, and on fluid-air interfaces; and the challenges of microrobot localization and control, in particular multi-robot control methods for magnetic microrobots. Finally, the book addresses current and future applications, including noninvasive medical diagnosis and treatment, environmental remediation, and scientific tools.

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Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]

Mobile Microrobotics By Metin Sitti - Chapter 1 (PDF) link (url) [BibTex]