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2011


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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]

2011

[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]


Model-Based Pose Estimation
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]


Illumination Estimation and Cast Shadow Detection through a Higher-order Graphical Model
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]


Pose-invariant 3{D} Proximal Femur Estimation through Bi-Planar Image  Segmentation with Hierarchical Higher-Order Graph-based Priors
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]


Intrinsic Dense 3{D} Surface Tracking
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]


Data-Driven Importance Distributions for Articulated Tracking
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]


A Physically Natural Metric for Human Motion and the Associated Brownian Motion Model
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]


Virtual Visual Servoing for Real-Time Robot Pose Estimation
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]


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


Discrete Minimum Distortion Correspondence Problems for Non-rigid   Shape Matching
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]


Viewpoint Invariant 3{D} Landmark Model Inference from Monocular 2{D}  Images Using Higher-Order Priors
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]


Predicting Articulated Human Motion from Spatial Processes
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]


An Empirical Study on the Performance of Spectral Manifold Learning Techniques
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]

2000


Probabilistic detection and tracking of motion boundaries
Probabilistic detection and tracking of motion boundaries

Black, M. J., Fleet, D. J.

Int. J. of Computer Vision, 38(3):231-245, July 2000 (article)

Abstract
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are represented using a non-linear generative model that 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 represent the posterior probability distribution over the model parameters given the image data using discrete samples. This distribution is propagated over time using a particle filtering algorithm. To efficiently represent such a high-dimensional space we initialize samples using the responses of a low-level motion discontinuity detector. The formulation and computational model provide a general probabilistic framework for motion estimation with multiple, non-linear, models.

pdf pdf from publisher Video [BibTex]

2000

pdf pdf from publisher Video [BibTex]


Stochastic tracking of {3D} human figures using {2D} image motion
Stochastic tracking of 3D human figures using 2D image motion

(Winner of the 2010 Koenderink Prize for Fundamental Contributions in Computer Vision)

Sidenbladh, H., Black, M. J., Fleet, D.

In European Conference on Computer Vision, ECCV, pages: 702-718, LNCS 1843, Springer Verlag, Dublin, Ireland, June 2000 (inproceedings)

Abstract
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appearance, a robust likelihood function based on image gray level differences, and a prior probability distribution over pose and joint angles that models how humans move. The posterior probability distribution over model parameters is represented using a discrete set of samples and is propagated over time using particle filtering. The approach extends previous work on parameterized optical flow estimation to exploit a complex 3D articulated motion model. It also extends previous work on human motion tracking by including a perspective camera model, by modeling limb self occlusion, and by recovering 3D motion from a monocular sequence. The explicit posterior probability distribution represents ambiguities due to image matching, model singularities, and perspective projection. The method relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.

pdf code [BibTex]

pdf code [BibTex]


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Functional analysis of human motion data

Ormoneit, D., Hastie, T., Black, M. J.

In In Proc. 5th World Congress of the Bernoulli Society for Probability and Mathematical Statistics and 63rd Annual Meeting of the Institute of Mathematical Statistics, Guanajuato, Mexico, May 2000 (inproceedings)

[BibTex]

[BibTex]


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Stochastic modeling and tracking of human motion

Ormoneit, D., Sidenbladh, H., Black, M. J., Hastie, T.

Learning 2000, Snowbird, UT, April 2000 (conference)

abstract [BibTex]

abstract [BibTex]


A framework for modeling the appearance of {3D} articulated figures
A framework for modeling the appearance of 3D articulated figures

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

In Int. Conf. on Automatic Face and Gesture Recognition, pages: 368-375, Grenoble, France, March 2000 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Design and use of linear models for image motion analysis
Design and use of linear models for image motion analysis

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

Int. J. of Computer Vision, 36(3):171-193, 2000 (article)

Abstract
Linear parameterized models of optical flow, particularly affine models, have become widespread in image motion analysis. The linear model coefficients are straightforward to estimate, and they provide reliable estimates of the optical flow of smooth surfaces. Here we explore the use of parameterized motion models that represent much more varied and complex motions. Our goals are threefold: to construct linear bases for complex motion phenomena; to estimate the coefficients of these linear models; and to recognize or classify image motions from the estimated coefficients. We consider two broad classes of motions: i) generic “motion features” such as motion discontinuities and moving bars; and ii) non-rigid, object-specific, motions such as the motion of human mouths. For motion features we construct a basis of steerable flow fields that approximate the motion features. For object-specific motions we construct basis flow fields from example motions using principal component analysis. In both cases, the model coefficients can be estimated directly from spatiotemporal image derivatives with a robust, multi-resolution scheme. Finally, we show how these model coefficients can be use to detect and recognize specific motions such as occlusion boundaries and facial expressions.

pdf [BibTex]

pdf [BibTex]


Robustly estimating changes in image appearance
Robustly estimating changes in image appearance

Black, M. J., Fleet, D. J., Yacoob, Y.

Computer Vision and Image Understanding, 78(1):8-31, 2000 (article)

Abstract
We propose a generalized model of image “appearance change” in which brightness variation over time is represented as a probabilistic mixture of different causes. We define four generative models of appearance change due to (1) object or camera motion; (2) illumination phenomena; (3) specular reflections; and (4) “iconic changes” which are specific to the objects being viewed. These iconic changes include complex occlusion events and changes in the material properties of the objects. We develop a robust statistical framework for recovering these appearance changes in image sequences. This approach generalizes previous work on optical flow to provide a richer description of image events and more reliable estimates of image motion in the presence of shadows and specular reflections.

pdf pdf from publisher DOI [BibTex]

pdf pdf from publisher DOI [BibTex]


Robust estimation of multiple surface shapes from occluded textures
Robust estimation of multiple surface shapes from occluded textures

Black, M. J., Rosenholtz, R.

In International Symposium on Computer Vision, pages: 485-490, Miami, FL, November 1995 (inproceedings)

pdf [BibTex]

pdf [BibTex]


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The PLAYBOT Project

Tsotsos, J. K., Dickinson, S., Jenkin, M., Milios, E., Jepson, A., Down, B., Amdur, E., Stevenson, S., Black, M., Metaxas, D., Cooperstock, J., Culhane, S., Nuflo, F., Verghese, G., Wai, W., Wilkes, D., Ye, Y.

In Proc. IJCAI Workshop on AI Applications for Disabled People, Montreal, August 1995 (inproceedings)

abstract [BibTex]

abstract [BibTex]


Recognizing facial expressions under rigid and non-rigid facial motions using local parametric models of image motion
Recognizing facial expressions under rigid and non-rigid facial motions using local parametric models of image motion

Black, M. J., Yacoob, Y.

In International Workshop on Automatic Face- and Gesture-Recognition, Zurich, July 1995 (inproceedings)

video abstract [BibTex]

video abstract [BibTex]


Image segmentation using robust mixture models
Image segmentation using robust mixture models

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

US Pat. 5,802,203, June 1995 (patent)

pdf on-line at USPTO [BibTex]


Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion
Tracking and recognizing rigid and non-rigid facial motions using local parametric models of image motion

Black, M. J., Yacoob, Y.

In Fifth International Conf. on Computer Vision, ICCV’95, pages: 347-381, Boston, MA, June 1995 (inproceedings)

Abstract
This paper explores the use of local parametrized models of image motion for recovering and recognizing the non-rigid and articulated motion of human faces. Parametric flow models (for example affine) are popular for estimating motion in rigid scenes. We observe that within local regions in space and time, such models not only accurately model non-rigid facial motions but also provide a concise description of the motion in terms of a small number of parameters. These parameters are intuitively related to the motion of facial features during facial expressions and we show how expressions such as anger, happiness, surprise, fear, disgust and sadness can be recognized from the local parametric motions in the presence of significant head motion. The motion tracking and expression recognition approach performs with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.

pdf video publisher site [BibTex]

pdf video publisher site [BibTex]


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A computational model for shape from texture for multiple textures

Black, M. J., Rosenholtz, R.

Investigative Ophthalmology and Visual Science Supplement, Vol. 36, No. 4, pages: 2202, March 1995 (conference)

abstract [BibTex]

abstract [BibTex]