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2011


Thumb xl hmdb snapshot1
HMDB: A Large Video Database for Human Motion Recognition

Kuhne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.

In IEEE International Conference on Computer Vision (ICCV), 2011 (inproceedings)

code, webpage, dataset pdf [BibTex]

2011

code, webpage, dataset pdf [BibTex]


Thumb xl screen shot 2012 03 13 at 2.41.46 pm
Dorsal Stream: From Algorithm to Neuroscience

Jhuang, H.

PhD Thesis, MIT, 2011 (techreport)

pdf [BibTex]


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Context dependent changes in grip selectivity in primate ventral premotor cortex

Franquemont, L., Vargas-Irwin, C., Black, M., Donoghue, J.

2011 Abstract Viewer and Itinerary Planner, Online, Society for Neuroscience, 2011, Online (conference)

[BibTex]

[BibTex]


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Towards a freely moving animal model: Combining markerless multi-camera video capture and wirelessly transmitted neural recording for the analysis of walking

Foster, J., Freifeld, O., Nuyujukian, P., Ryu, S., Black, M., Shenoy, K.

2011 Abstract Viewer and Itinerary Planner, Society for Neuroscience, 2011, Online (conference)

Project Page [BibTex]

Project Page [BibTex]


Thumb xl ijnmbe1
Modelling pipeline for subject-specific arterial blood flow—A review

Igor Sazonov, Si Yong Yeo, Rhodri Bevan, Xianghua Xie, Raoul van Loon, Perumal Nithiarasu

International Journal for Numerical Methods in Biomedical Engineering, 27(12):1868–1910, 2011 (article)

Abstract
In this paper, a robust and semi-automatic modelling pipeline for blood flow through subject-specific arterial geometries is presented. The framework developed consists of image segmentation, domain discretization (meshing) and fluid dynamics. All the three subtopics of the pipeline are explained using an example of flow through a severely stenosed human carotid artery. In the Introduction, the state-of-the-art of both image segmentation and meshing is presented in some detail, and wherever possible the advantages and disadvantages of the existing methods are analysed. Followed by this, the deformable model used for image segmentation is presented. This model is based upon a geometrical potential force (GPF), which is a function of the image. Both the GPF calculation and level set determination are explained. Following the image segmentation method, a semi-automatic meshing method used in the present study is explained in full detail. All the relevant techniques required to generate a valid domain discretization are presented. These techniques include generating a valid surface mesh, skeletonization, mesh cropping, boundary layer mesh construction and various mesh cosmetic methods that are essential for generating a high-quality domain discretization. After presenting the mesh generation procedure, how to generate flow boundary conditions for both the inlets and outlets of a geometry is explained in detail. This is followed by a brief note on the flow solver, before studying the blood flow through the carotid artery with a severe stenosis.

[BibTex]

[BibTex]


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Geometrically Induced Force Interaction for Three-Dimensional Deformable Models

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

IEEE Transactions on Image Processing, 20(5):1373 - 1387, 2011 (article)

Abstract
In this paper, we propose a novel 3-D deformable model that is based upon a geometrically induced external force field which can be conveniently generalized to arbitrary dimensions. This external force field is based upon hypothesized interactions between the relative geometries of the deformable model and the object boundary characterized by image gradient. The evolution of the deformable model is solved using the level set method so that topological changes are handled automatically. The relative geometrical configurations between the deformable model and the object boundaries contribute to a dynamic vector force field that changes accordingly as the deformable model evolves. The geometrically induced dynamic interaction force has been shown to greatly improve the deformable model performance in acquiring complex geometries and highly concave boundaries, and it gives the deformable model a high invariancy in initialization configurations. The voxel interactions across the whole image domain provide a global view of the object boundary representation, giving the external force a long attraction range. The bidirectionality of the external force field allows the new deformable model to deal with arbitrary cross-boundary initializations, and facilitates the handling of weak edges and broken boundaries. In addition, we show that by enhancing the geometrical interaction field with a nonlocal edge-preserving algorithm, the new deformable model can effectively overcome image noise. We provide a comparative study on the segmentation of various geometries with different topologies from both synthetic and real images, and show that the proposed method achieves significant improvements against existing image gradient techniques.

[BibTex]

[BibTex]


Thumb xl dagm2011imagesmall
Shape and pose-invariant correspondences using probabilistic geodesic surface embedding

Tsoli, A., Black, M. J.

In 33rd Annual Symposium of the German Association for Pattern Recognition (DAGM), 6835, pages: 256-265, Lecture Notes in Computer Science, (Editors: Mester, Rudolf and Felsberg, Michael), Springer, 2011 (inproceedings)

Abstract
Correspondence between non-rigid deformable 3D objects provides a foundation for object matching and retrieval, recognition, and 3D alignment. Establishing 3D correspondence is challenging when there are non-rigid deformations or articulations between instances of a class. We present a method for automatically finding such correspondences that deals with significant variations in pose, shape and resolution between pairs of objects.We represent objects as triangular meshes and consider normalized geodesic distances as representing their intrinsic characteristics. Geodesic distances are invariant to pose variations and nearly invariant to shape variations when properly normalized. The proposed method registers two objects by optimizing a joint probabilistic model over a subset of vertex pairs between the objects. The model enforces preservation of geodesic distances between corresponding vertex pairs and inference is performed using loopy belief propagation in a hierarchical scheme. Additionally our method prefers solutions in which local shape information is consistent at matching vertices. We quantitatively evaluate our method and show that is is more accurate than a state of the art method.

pdf talk Project Page [BibTex]

pdf talk Project Page [BibTex]


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Steerable random fields for image restoration and inpainting

Roth, S., Black, M. J.

In Markov Random Fields for Vision and Image Processing, pages: 377-387, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

Abstract
This chapter introduces the concept of a Steerable Random Field (SRF). In contrast to traditional Markov random field (MRF) models in low-level vision, the random field potentials of a SRF are defined in terms of filter responses that are steered to the local image structure. This steering uses the structure tensor to obtain derivative responses that are either aligned with, or orthogonal to, the predominant local image structure. Analysis of the statistics of these steered filter responses in natural images leads to the model proposed here. Clique potentials are defined over steered filter responses using a Gaussian scale mixture model and are learned from training data. The SRF model connects random fields with anisotropic regularization and provides a statistical motivation for the latter. Steering the random field to the local image structure improves image denoising and inpainting performance compared with traditional pairwise MRFs.

publisher site [BibTex]

publisher site [BibTex]


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Spatial Models of Human Motion

Soren Hauberg

University of Copenhagen, 2011 (phdthesis)

PDF [BibTex]

PDF [BibTex]


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Visual orientation and direction selectivity through thalamic synchrony

Kelly, S., Stanley, G., Jin, J., Wang, Y., Desbordes, G., Wang, Q., Black, M., Alonso, J.

2011 Abstract Viewer and Itinerary Planner, Society for Neuroscience, 2011, Online (conference)

[BibTex]

[BibTex]


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Use of the BrainGate neural inteface system for more than five years by a woman with tetraplegia

Hochberg, L., Bacher, D., Barefoot, L., Berhanu, E., Black, M., Cash, S., Feldman, J., Gallivan, E., Homer, M., Jarosiewicz, B., King, B., Liu, J., Malik, W., Masse, N., Berge, J., Rosler, D., Schmansky, N., Simeral, J., Travers, B., Truccolo, W., Donoghue, J.

2011 Abstract Viewer and Itinerary Planner, Society for Neuroscience, 2011, Onine (conference)

[BibTex]

[BibTex]


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Extracting 3D Structures from Biomedical Data

Xianghua Xie, Si Yong Yeo, Igor Sazonov, Perumal Nithiarasu

Proceedings of the 5th International Conference on Bioinformatics and Biomedical Engineering, 2011 (conference)

[BibTex]

[BibTex]


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Model-Based Pose Estimation

Pons-Moll, G., Rosenhahn, B.

In Visual Analysis of Humans: Looking at People, pages: 139-170, 9, (Editors: T. Moeslund, A. Hilton, V. Krueger, L. Sigal), Springer, 2011 (inbook)

book page pdf [BibTex]

book page pdf [BibTex]


Thumb xl illumination cvpr11
Illumination Estimation and Cast Shadow Detection through a Higher-order Graphical Model

Panagopoulos, A., Wang, C., Samaras, D., Paragios, N.

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl femursegmentation miccai11
Pose-invariant 3D Proximal Femur Estimation through Bi-Planar Image Segmentation with Hierarchical Higher-Order Graph-based Priors

Wang, C., Boussaid, H., Simon, L., Lazennec, J., Paragios, N.

In International Conference, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2011 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl sufacetracking cvpr11
Intrinsic Dense 3D Surface Tracking

Zeng, Y., Wang, C., Wang, Y., Gu, X., Samaras, D., Paragios, N.

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl emmcvpr2012
Data-Driven Importance Distributions for Articulated Tracking

Soren Hauberg, Kim S. Pedersen

In Energy Minimization Methods in Computer Vision and Pattern Recognition, 6819, pages: 287-299, Lecture Notes in Computer Science, (Editors: Boykov, Yuri and Kahl, Fredrik and Lempitsky, Victor and Schmidt, Frank), Springer Berlin Heidelberg, 2011 (inproceedings)

Publishers site Code PDF Suppl. material [BibTex]

Publishers site Code PDF Suppl. material [BibTex]


Thumb xl kdcv2011 teaser
A Physically Natural Metric for Human Motion and the Associated Brownian Motion Model

Soren Hauberg, Kim Steenstrup Pedersen

In 1st IEEE Workshop on Kernels and Distances for Computer Vision (ICCV workshop), 2011 (inproceedings)

Workshop link [BibTex]

Workshop link [BibTex]


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Virtual Visual Servoing for Real-Time Robot Pose Estimation

Gratal, X., Romero, J., Kragic, D.

In International Federation of Automatic Control World Congress, IFAC, 2011 (inproceedings)

Pdf [BibTex]

Pdf [BibTex]


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Cooperative Localization Based on Visually Shared Objects

Lima, P., Santos, P., Oliveira, R., Ahmad, A., Santos, J.

In RoboCup 2010: Robot Soccer World Cup XIV, pages: 350-361, Lecture Notes in Computer Science ; 6556, Springer, Berlin, Germany, 2011 (inproceedings)

Abstract
In this paper we describe a cooperative localization algorithm based on a modification of the Monte Carlo Localization algorithm where, when a robot detects it is lost, particles are spread not uniformly in the state space, but rather according to the information on the location of an object whose distance and bearing is measured by the lost robot. The object location is provided by other robots of the same team using explicit (wireless) communication. Results of application of the method to a team of real robots are presented.

DOI [BibTex]

DOI [BibTex]


Thumb xl ijnmbe1
Computational flow studies in a subject-specific human upper airway using a one-equation turbulence model. Influence of the nasal cavity

Prihambodo Saksono, Perumal Nithiarasu, Igor Sazonov, Si Yong Yeo

International Journal for Numerical Methods in Biomedical Engineering, 87(1-5):96–114, 2011 (article)

Abstract
This paper focuses on the impact of including nasal cavity on airflow through a human upper respiratory tract. A computational study is carried out on a realistic geometry, reconstructed from CT scans of a subject. The geometry includes nasal cavity, pharynx, larynx, trachea and two generations of airway bifurcations below trachea. The unstructured mesh generation procedure is discussed in some length due to the complex nature of the nasal cavity structure and poor scan resolution normally available from hospitals. The fluid dynamic studies have been carried out on the geometry with and without the inclusion of the nasal cavity. The characteristic-based split scheme along with the one-equation Spalart–Allmaras turbulence model is used in its explicit form to obtain flow solutions at steady state. Results reveal that the exclusion of nasal cavity significantly influences the resulting solution. In particular, the location of recirculating flow in the trachea is dramatically different when the truncated geometry is used. In addition, we also address the differences in the solution due to imposed, equally distributed and proportionally distributed flow rates at inlets (both nares). The results show that the differences in flow pattern between the two inlet conditions are not confined to the nasal cavity and nasopharyngeal region, but they propagate down to the trachea.

[BibTex]

[BibTex]


Thumb xl sufacematching ssvm11
Discrete Minimum Distortion Correspondence Problems for Non-rigid Shape Matching

Wang, C., Bronstein, M. M., Bronstein, A. M., Paragios, N.

In International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2011 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl viewpointinvariantmodel iccv11.
Viewpoint Invariant 3D Landmark Model Inference from Monocular 2D Images Using Higher-Order Priors

Wang, C., Zeng, Y., Simon, L., Kakadiaris, I., Samaras, D., Paragios, N.

In IEEE International Conference on Computer Vision (ICCV), 2011 (inproceedings)

pdf [BibTex]

pdf [BibTex]


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Correspondence estimation from non-rigid motion information

Wulff, J., Lotz, T., Stehle, T., Aach, T., Chase, J. G.

In Proc. SPIE, Proc. SPIE, (Editors: B. M. Dawant, D. R. Haynor), SPIE, 2011 (inproceedings)

Abstract
The DIET (Digital Image Elasto Tomography) system is a novel approach to screen for breast cancer using only optical imaging information of the surface of a vibrating breast. 3D tracking of skin surface motion without the requirement of external markers is desirable. A novel approach to establish point correspondences using pure skin images is presented here. Instead of the intensity, motion is used as the primary feature, which can be extracted using optical flow algorithms. Taking sequences of multiple frames into account, this motion information alone is accurate and unambiguous enough to allow for a 3D reconstruction of the breast surface. Two approaches, direct and probabilistic, for this correspondence estimation are presented here, suitable for different levels of calibration information accuracy. Reconstructions show that the results obtained using these methods are comparable in accuracy to marker-based methods while considerably increasing resolution. The presented method has high potential in optical tissue deformation and motion sensing.

pdf link (url) DOI [BibTex]

pdf link (url) DOI [BibTex]


Thumb xl ijcv2012
Predicting Articulated Human Motion from Spatial Processes

Soren Hauberg, Kim S. Pedersen

International Journal of Computer Vision, 94, pages: 317-334, Springer Netherlands, 2011 (article)

Publishers site Code Paper site PDF [BibTex]

Publishers site Code Paper site PDF [BibTex]


Thumb xl icann2011
An Empirical Study on the Performance of Spectral Manifold Learning Techniques

Peter Mysling, Soren Hauberg, Kim S. Pedersen

In Artificial Neural Networks and Machine Learning – ICANN 2011, 6791, pages: 347-354, Lecture Notes in Computer Science, (Editors: Honkela, Timo and Duch, Włodzisław and Girolami, Mark and Kaski, Samuel), Springer Berlin Heidelberg, 2011 (inproceedings)

Publishers site PDF [BibTex]

Publishers site PDF [BibTex]


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Separation of visual object features and grasp strategy in primate ventral premotor cortex

Vargas-Irwin, C., Franquemont, L., Black, M., Donoghue, J.

Neural Control of Movement, 21st Annual Conference, 2011 (conference)

[BibTex]

[BibTex]

2002


Thumb xl bildschirmfoto 2013 01 15 um 09.54.19
Inferring hand motion from multi-cell recordings in motor cortex using a Kalman filter

Wu, W., Black, M. J., Gao, Y., Bienenstock, E., Serruya, M., Donoghue, J. P.

In SAB’02-Workshop on Motor Control in Humans and Robots: On the Interplay of Real Brains and Artificial Devices, pages: 66-73, Edinburgh, Scotland (UK), August 2002 (inproceedings)

pdf [BibTex]

2002

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 15 um 10.33.56
Bayesian Inference of Visual Motion Boundaries

Fleet, D. J., Black, M. J., Nestares, O.

In Exploring Artificial Intelligence in the New Millennium, pages: 139-174, (Editors: Lakemeyer, G. and Nebel, B.), Morgan Kaufmann Pub., July 2002 (incollection)

Abstract
This chapter addresses an open problem in visual motion analysis, the estimation of image motion in the vicinity of occlusion boundaries. With a Bayesian formulation, local image motion is explained in terms of multiple, competing, nonlinear models, including models for smooth (translational) motion and for motion boundaries. The generative model for motion boundaries explicitly encodes the orientation of the boundary, the velocities on either side, the motion of the occluding edge over time, and the appearance/disappearance of pixels at the boundary. We formulate the posterior probability distribution over the models and model parameters, conditioned on the image sequence. Approximate inference is achieved with a combination of tools: A Bayesian filter provides for online computation; factored sampling allows us to represent multimodal non-Gaussian distributions and to propagate beliefs with nonlinear dynamics from one time to the next; and mixture models are used to simplify the computation of joint prediction distributions in the Bayesian filter. To efficiently represent such a high-dimensional space, we also initialize samples using the responses of a low-level motion-discontinuity detector. The basic formulation and computational model provide a general probabilistic framework for motion estimation with multiple, nonlinear models.

pdf [BibTex]

pdf [BibTex]


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Inferring hand motion from multi-cell recordings in motor cortex using a Kalman filter

Wu, W., Black M., Gao, Y., Bienenstock, E., Serruya, M., Donoghue, J.

Program No. 357.5. 2002 Abstract Viewer/Itinerary Planner, Society for Neuroscience, Washington, DC, 2002, Online (conference)

abstract [BibTex]

abstract [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 09.50.58
Automatic detection and tracking of human motion with a view-based representation

Fablet, R., Black, M. J.

In European Conf. on Computer Vision, ECCV 2002, 1, pages: 476-491, LNCS 2353, (Editors: A. Heyden and G. Sparr and M. Nielsen and P. Johansen), Springer-Verlag , 2002 (inproceedings)

Abstract
This paper proposes a solution for the automatic detection and tracking of human motion in image sequences. Due to the complexity of the human body and its motion, automatic detection of 3D human motion remains an open, and important, problem. Existing approaches for automatic detection and tracking focus on 2D cues and typically exploit object appearance (color distribution, shape) or knowledge of a static background. In contrast, we exploit 2D optical flow information which provides rich descriptive cues, while being independent of object and background appearance. To represent the optical flow patterns of people from arbitrary viewpoints, we develop a novel representation of human motion using low-dimensional spatio-temporal models that are learned using motion capture data of human subjects. In addition to human motion (the foreground) we probabilistically model the motion of generic scenes (the background); these statistical models are defined as Gibbsian fields specified from the first-order derivatives of motion observations. Detection and tracking are posed in a principled Bayesian framework which involves the computation of a posterior probability distribution over the model parameters (i.e., the location and the type of the human motion) given a sequence of optical flow observations. Particle filtering is used to represent and predict this non-Gaussian posterior distribution over time. The model parameters of samples from this distribution are related to the pose parameters of a 3D articulated model (e.g. the approximate joint angles and movement direction). Thus the approach proves suitable for initializing more complex probabilistic models of human motion. As shown by experiments on real image sequences, our method is able to detect and track people under different viewpoints with complex backgrounds.

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 10.06.33
A layered motion representation with occlusion and compact spatial support

Fleet, D. J., Jepson, A., Black, M. J.

In European Conf. on Computer Vision, ECCV 2002, 1, pages: 692-706, LNCS 2353, (Editors: A. Heyden and G. Sparr and M. Nielsen and P. Johansen), Springer-Verlag , 2002 (inproceedings)

Abstract
We describe a 2.5D layered representation for visual motion analysis. The representation provides a global interpretation of image motion in terms of several spatially localized foreground regions along with a background region. Each of these regions comprises a parametric shape model and a parametric motion model. The representation also contains depth ordering so visibility and occlusion are rightly included in the estimation of the model parameters. Finally, because the number of objects, their positions, shapes and sizes, and their relative depths are all unknown, initial models are drawn from a proposal distribution, and then compared using a penalized likelihood criterion. This allows us to automatically initialize new models, and to compare different depth orderings.

pdf [BibTex]

pdf [BibTex]


Thumb xl eccv2002hvg
Implicit probabilistic models of human motion for synthesis and tracking

Sidenbladh, H., Black, M. J., Sigal, L.

In European Conf. on Computer Vision, 1, pages: 784-800, 2002 (inproceedings)

Abstract
This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an explicit probabilistic model from available training data is currently impractical. Instead we exploit methods from texture synthesis that treat images as representing an implicit empirical distribution. These methods replace the problem of representing the probability of a texture pattern with that of searching the training data for similar instances of that pattern. We extend this idea to temporal data representing 3D human motion with a large database of example motions. To make the method useful in practice, we must address the problem of efficient search in a large training set; efficiency is particularly important for tracking. Towards that end, we learn a low dimensional linear model of human motion that is used to structure the example motion database into a binary tree. An approximate probabilistic tree search method exploits the coefficients of this low-dimensional representation and runs in sub-linear time. This probabilistic tree search returns a particular sample human motion with probability approximating the true distribution of human motions in the database. This sampling method is suitable for use with particle filtering techniques and is applied to articulated 3D tracking of humans within a Bayesian framework. Successful tracking results are presented, along with examples of synthesizing human motion using the model.

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 10.29.56
Robust parameterized component analysis: Theory and applications to 2D facial modeling

De la Torre, F., Black, M. J.

In European Conf. on Computer Vision, ECCV 2002, 4, pages: 653-669, LNCS 2353, Springer-Verlag, 2002 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 15 um 10.03.10
Probabilistic inference of hand motion from neural activity in motor cortex

Gao, Y., Black, M. J., Bienenstock, E., Shoham, S., Donoghue, J.

In Advances in Neural Information Processing Systems 14, pages: 221-228, MIT Press, 2002 (inproceedings)

pdf [BibTex]

pdf [BibTex]