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2014


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Advanced Structured Prediction

Nowozin, S., Gehler, P. V., Jancsary, J., Lampert, C. H.

Advanced Structured Prediction, pages: 432, Neural Information Processing Series, MIT Press, November 2014 (book)

Abstract
The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components. These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning.

publisher link (url) [BibTex]

2014

publisher link (url) [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.

PDF [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.

[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.

[BibTex]

[BibTex]


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Human Pose Estimation from Video and Inertial Sensors

Pons-Moll, G.

Ph.D Thesis, -, 2014 (book)

Abstract
The analysis and understanding of human movement is central to many applications such as sports science, medical diagnosis and movie production. The ability to automatically monitor human activity in security sensitive areas such as airports, lobbies or borders is of great practical importance. Furthermore, automatic pose estimation from images leverages the processing and understanding of massive digital libraries available on the Internet. We build upon a model based approach where the human shape is modelled with a surface mesh and the motion is parametrized by a kinematic chain. We then seek for the pose of the model that best explains the available observations coming from different sensors. In a first scenario, we consider a calibrated mult-iview setup in an indoor studio. To obtain very accurate results, we propose a novel tracker that combines information coming from video and a small set of Inertial Measurement Units (IMUs). We do so by locally optimizing a joint energy consisting of a term that measures the likelihood of the video data and a term for the IMU data. This is the first work to successfully combine video and IMUs information for full body pose estimation. When compared to commercial marker based systems the proposed solution is more cost efficient and less intrusive for the user. In a second scenario, we relax the assumption of an indoor studio and we tackle outdoor scenes with background clutter, illumination changes, large recording volumes and difficult motions of people interacting with objects. Again, we combine information from video and IMUs. Here we employ a particle based optimization approach that allows us to be more robust to tracking failures. To satisfy the orientation constraints imposed by the IMUs, we derive an analytic Inverse Kinematics (IK) procedure to sample from the manifold of valid poses. The generated hypothesis come from a lower dimensional manifold and therefore the computational cost can be reduced. Experiments on challenging sequences suggest the proposed tracker can be applied to capture in outdoor scenarios. Furthermore, the proposed IK sampling procedure can be used to integrate any kind of constraints derived from the environment. Finally, we consider the most challenging possible scenario: pose estimation of monocular images. Here, we argue that estimating the pose to the degree of accuracy as in an engineered environment is too ambitious with the current technology. Therefore, we propose to extract meaningful semantic information about the pose directly from image features in a discriminative fashion. In particular, we introduce posebits which are semantic pose descriptors about the geometric relationships between parts in the body. The experiments show that the intermediate step of inferring posebits from images can improve pose estimation from monocular imagery. Furthermore, posebits can be very useful as input feature for many computer vision algorithms.

pdf [BibTex]


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Simulated Annealing

Gall, J.

In Encyclopedia of Computer Vision, pages: 737-741, 0, (Editors: Ikeuchi, K. ), Springer Verlag, 2014, to appear (inbook)

[BibTex]

[BibTex]

2012


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Coregistration: Supplemental Material

Hirshberg, D., Loper, M., Rachlin, E., Black, M. J.

(No. 4), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf [BibTex]

2012

pdf [BibTex]


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Lie Bodies: A Manifold Representation of 3D Human Shape. Supplemental Material

Freifeld, O., Black, M. J.

(No. 5), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf Project Page [BibTex]

pdf Project Page [BibTex]


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MPI-Sintel Optical Flow Benchmark: Supplemental Material

Butler, D. J., Wulff, J., Stanley, G. B., Black, M. J.

(No. 6), Max Planck Institute for Intelligent Systems, October 2012 (techreport)

pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Exploiting pedestrian interaction via global optimization and social behaviors

Leal-Taixé, L., Pons-Moll, G., Rosenhahn, B.

In Theoretic Foundations of Computer Vision: Outdoor and Large-Scale Real-World Scene Analysis, Springer, April 2012 (incollection)

pdf [BibTex]

pdf [BibTex]


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HUMIM Software for Articulated Tracking

Soren Hauberg, Kim S. Pedersen

(01/2012), Department of Computer Science, University of Copenhagen, January 2012 (techreport)

Code PDF [BibTex]

Code PDF [BibTex]


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A geometric framework for statistics on trees

Aasa Feragen, Mads Nielsen, Soren Hauberg, Pechin Lo, Marleen de Bruijne, Francois Lauze

(11/02), Department of Computer Science, University of Copenhagen, January 2012 (techreport)

PDF [BibTex]

PDF [BibTex]


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Data-driven Manifolds for Outdoor Motion Capture

Pons-Moll, G., Leal-Taix’e, L., Gall, J., Rosenhahn, B.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 305-328, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

video publisher's site pdf Project Page [BibTex]

video publisher's site pdf Project Page [BibTex]


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Scan-Based Flow Modelling in Human Upper Airways

Perumal Nithiarasu, Igor Sazonov, Si Yong Yeo

In Patient-Specific Modeling in Tomorrow’s Medicine, pages: 241 - 280, 0, (Editors: Amit Gefen), Springer, 2012 (inbook)

[BibTex]

[BibTex]


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An Introduction to Random Forests for Multi-class Object Detection

Gall, J., Razavi, N., van Gool, L.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 243-263, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

code code for Hough forest publisher's site pdf Project Page [BibTex]

code code for Hough forest publisher's site pdf Project Page [BibTex]


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Home 3D body scans from noisy image and range data

Weiss, A., Hirshberg, D., Black, M. J.

In Consumer Depth Cameras for Computer Vision: Research Topics and Applications, pages: 99-118, 6, (Editors: Andrea Fossati and Juergen Gall and Helmut Grabner and Xiaofeng Ren and Kurt Konolige), Springer-Verlag, 2012 (incollection)

Project Page [BibTex]

Project Page [BibTex]


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Consumer Depth Cameras for Computer Vision - Research Topics and Applications

Fossati, A., Gall, J., Grabner, H., Ren, X., Konolige, K.

Advances in Computer Vision and Pattern Recognition, Springer, 2012 (book)

workshop publisher's site [BibTex]

workshop publisher's site [BibTex]

2007


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Probabilistically modeling and decoding neural population activity in motor cortex

Black, M. J., Donoghue, J. P.

In Toward Brain-Computer Interfacing, pages: 147-159, (Editors: Dornhege, G. and del R. Millan, J. and Hinterberger, T. and McFarland, D. and Muller, K.-R.), MIT Press, London, 2007 (incollection)

pdf [BibTex]

2007

pdf [BibTex]


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Denoising archival films using a learned Bayesian model

Moldovan, T. M., Roth, S., Black, M. J.

(CS-07-03), Brown University, Department of Computer Science, 2007 (techreport)

pdf [BibTex]

pdf [BibTex]

2006


Thumb xl screen shot 2012 06 06 at 11.31.38 am
Implicit Wiener Series, Part II: Regularised estimation

Gehler, P., Franz, M.

(148), Max Planck Institute, 2006 (techreport)

pdf [BibTex]

2006


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HumanEva: Synchronized video and motion capture dataset for evaluation of articulated human motion

Sigal, L., Black, M. J.

(CS-06-08), Brown University, Department of Computer Science, 2006 (techreport)

pdf abstract [BibTex]

pdf abstract [BibTex]


Thumb xl screen shot 2012 06 06 at 11.15.02 am
Products of “Edge-perts”

Gehler, P., Welling, M.

In Advances in Neural Information Processing Systems 18, pages: 419-426, (Editors: Weiss, Y. and Sch"olkopf, B. and Platt, J.), MIT Press, Cambridge, MA, 2006 (incollection)

pdf [BibTex]

pdf [BibTex]