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2005


Representing cyclic human motion using functional analysis
Representing cyclic human motion using functional analysis

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

Image and Vision Computing, 23(14):1264-1276, December 2005 (article)

Abstract
We present a robust automatic method for modeling cyclic 3D human motion such as walking using motion-capture data. The pose of the body is represented by a time-series of joint angles which are automatically segmented into a sequence of motion cycles. The mean and the principal components of these cycles are computed using a new algorithm that enforces smooth transitions between the cycles by operating in the Fourier domain. Key to this method is its ability to automatically deal with noise and missing data. A learned walking model is then exploited for Bayesian tracking of 3D human motion.

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pdf pdf from publisher DOI [BibTex]

2005


pdf pdf from publisher DOI [BibTex]


A quantitative evaluation of video-based {3D} person tracking
A quantitative evaluation of video-based 3D person tracking

Balan, A. O., Sigal, L., Black, M. J.

In The Second Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS, pages: 349-356, October 2005 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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Perception of Curvature and Object Motion Via Contact Location Feedback

Provancher, W. R., Kuchenbecker, K. J., Niemeyer, G., Cutkosky, M. R.

In Proceedings of the International Symposium on Robotics Research (ISRR), 15, pages: 456-465, Springer Tracts in Advanced Robotics, Springer, Siena, Italy, 2005, Oral presentation given by Provancher in October of 2003 (inproceedings)

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[BibTex]

[BibTex]


Inferring attentional state and kinematics from motor cortical firing rates
Inferring attentional state and kinematics from motor cortical firing rates

Wood, F., Prabhat, , Donoghue, J. P., Black, M. J.

In Proc. IEEE Engineering in Medicine and Biology Society, pages: 1544-1547, September 2005 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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Contact Location Display for Haptic Perception of Curvature and Object Motion

Provancher, W. R., Cutkosky, M. R., Kuchenbecker, K. J., Niemeyer, G.

International Journal of Robotics Research, 24(9):691-702, sep 2005 (article)

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[BibTex]

[BibTex]


Motor cortical decoding using an autoregressive moving average model
Motor cortical decoding using an autoregressive moving average model

Fisher, J., Black, M. J.

In Proc. IEEE Engineering in Medicine and Biology Society, pages: 1469-1472, September 2005 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


Fields of Experts: A framework for learning image priors
Fields of Experts: A framework for learning image priors

Roth, S., Black, M. J.

In IEEE Conf. on Computer Vision and Pattern Recognition, 2, pages: 860-867, June 2005 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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Modeling Induced Master Motion in Force-Reflecting Teleoperation

Kuchenbecker, K. J., Niemeyer, G.

In Proc. IEEE International Conference on Robotics and Automation, pages: 348-353, Barcelona, Spain, April 2005, Oral presentation given by Kuchenbecker (inproceedings)

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[BibTex]

[BibTex]


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Event-Based Haptics and Acceleration Matching: Portraying and Assessing the Realism of Contact

Kuchenbecker, K. J., Fiene, J. P., Niemeyer, G.

In Proc. IEEE World Haptics Conference, pages: 381-387, Pisa, Italy, March 2005, Oral presentation given by Kuchenbecker (inproceedings)

hi

[BibTex]

[BibTex]


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Event-Based Haptic Feedback

Kuchenbecker, K. J., Fiene, J. P., Niemeyer, G.

Hands-on demonstration at IEEE World Haptics Conference, Pisa, Italy, March 2005 (misc)

hi

[BibTex]

[BibTex]


A Flow-Based Approach to Vehicle Detection and Background Mosaicking in Airborne Video
A Flow-Based Approach to Vehicle Detection and Background Mosaicking in Airborne Video

Yalcin, H. C. R. B. M. J. H. M.

IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Video Proceedings,, pages: 1202, 2005 (patent)

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YouTube pdf [BibTex]

YouTube pdf [BibTex]


On the spatial statistics of optical flow
On the spatial statistics of optical flow

(Marr Prize, Honorable Mention)

Roth, S., Black, M. J.

In International Conf. on Computer Vision, pages: 42-49, 2005 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


Modeling neural population spiking activity with {Gibbs} distributions
Modeling neural population spiking activity with Gibbs distributions

Wood, F., Roth, S., Black, M. J.

In Advances in Neural Information Processing Systems 18, pages: 1537-1544, 2005 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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Energy-based models of motor cortical population activity

Wood, F., Black, M.

Program No. 689.20. 2005 Abstract Viewer/Itinerary Planner, Society for Neuroscience, Washington, DC, 2005 (conference)

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abstract [BibTex]

abstract [BibTex]

1996


Cardboard people: A parameterized model of articulated motion
Cardboard people: A parameterized model of articulated motion

Ju, S. X., Black, M. J., Yacoob, Y.

In 2nd Int. Conf. on Automatic Face- and Gesture-Recognition, pages: 38-44, Killington, Vermont, October 1996 (inproceedings)

Abstract
We extend the work of Black and Yacoob on the tracking and recognition of human facial expressions using parameterized models of optical flow to deal with the articulated motion of human limbs. We define a "cardboard person model" in which a person's limbs are represented by a set of connected planar patches. The parameterized image motion of these patches is constrained to enforce articulated motion and is solved for directly using a robust estimation technique. The recovered motion parameters provide a rich and concise description of the activity that can be used for recognition. We propose a method for performing view-based recognition of human activities from the optical flow parameters that extends previous methods to cope with the cyclical nature of human motion. We illustrate the method with examples of tracking human legs over long image sequences.

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pdf [BibTex]

1996


pdf [BibTex]


Estimating optical flow in segmented images using variable-order parametric models with local deformations
Estimating optical flow in segmented images using variable-order parametric models with local deformations

Black, M. J., Jepson, A.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(10):972-986, October 1996 (article)

Abstract
This paper presents a new model for estimating optical flow based on the motion of planar regions plus local deformations. The approach exploits brightness information to organize and constrain the interpretation of the motion by using segmented regions of piecewise smooth brightness to hypothesize planar regions in the scene. Parametric flow models are estimated in these regions in a two step process which first computes a coarse fit and estimates the appropriate parameterization of the motion of the region (two, six, or eight parameters). The initial fit is refined using a generalization of the standard area-based regression approaches. Since the assumption of planarity is likely to be violated, we allow local deformations from the planar assumption in the same spirit as physically-based approaches which model shape using coarse parametric models plus local deformations. This parametric+deformation model exploits the strong constraints of parametric approaches while retaining the adaptive nature of regularization approaches. Experimental results on a variety of images indicate that the parametric+deformation model produces accurate flow estimates while the incorporation of brightness segmentation provides precise localization of motion boundaries.

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pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


On the unification of line processes, outlier rejection, and robust statistics with applications in early vision
On the unification of line processes, outlier rejection, and robust statistics with applications in early vision

Black, M., Rangarajan, A.

International Journal of Computer Vision , 19(1):57-92, July 1996 (article)

Abstract
The modeling of spatial discontinuities for problems such as surface recovery, segmentation, image reconstruction, and optical flow has been intensely studied in computer vision. While “line-process” models of discontinuities have received a great deal of attention, there has been recent interest in the use of robust statistical techniques to account for discontinuities. This paper unifies the two approaches. To achieve this we generalize the notion of a “line process” to that of an analog “outlier process” and show how a problem formulated in terms of outlier processes can be viewed in terms of robust statistics. We also characterize a class of robust statistical problems for which an equivalent outlier-process formulation exists and give a straightforward method for converting a robust estimation problem into an outlier-process formulation. We show how prior assumptions about the spatial structure of outliers can be expressed as constraints on the recovered analog outlier processes and how traditional continuation methods can be extended to the explicit outlier-process formulation. These results indicate that the outlier-process approach provides a general framework which subsumes the traditional line-process approaches as well as a wide class of robust estimation problems. Examples in surface reconstruction, image segmentation, and optical flow are presented to illustrate the use of outlier processes and to show how the relationship between outlier processes and robust statistics can be exploited. An appendix provides a catalog of common robust error norms and their equivalent outlier-process formulations.

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pdf pdf from publisher DOI [BibTex]


Skin and Bones: Multi-layer, locally affine, optical flow and regularization with transparency
Skin and Bones: Multi-layer, locally affine, optical flow and regularization with transparency

(Nominated: Best paper)

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

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR’96, pages: 307-314, San Francisco, CA, June 1996 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


EigenTracking: Robust matching and tracking of articulated objects using a view-based representation
EigenTracking: Robust matching and tracking of articulated objects using a view-based representation

Black, M. J., Jepson, A.

In Proc. Fourth European Conf. on Computer Vision, ECCV’96, pages: 329-342, LNCS 1064, Springer Verlag, Cambridge, England, April 1996 (inproceedings)

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pdf video [BibTex]

pdf video [BibTex]


Mixture Models for Image Representation
Mixture Models for Image Representation

Jepson, A., Black, M.

PRECARN ARK Project Technical Report ARK96-PUB-54, March 1996 (techreport)

Abstract
We consider the estimation of local greylevel image structure in terms of a layered representation. This type of representation has recently been successfully used to segment various objects from clutter using either optical ow or stereo disparity information. We argue that the same type of representation is useful for greylevel data in that it allows for the estimation of properties for each of several different components without prior segmentation. Our emphasis in this paper is on the process used to extract such a layered representation from a given image In particular we consider a variant of the EM algorithm for the estimation of the layered model and consider a novel technique for choosing the number of layers to use. We briefly consider the use of a simple version of this approach for image segmentation and suggest two potential applications to the ARK project

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pdf [BibTex]

pdf [BibTex]


The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields
The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields

Black, M. J., Anandan, P.

Computer Vision and Image Understanding, 63(1):75-104, January 1996 (article)

Abstract
Most approaches for estimating optical flow assume that, within a finite image region, only a single motion is present. This single motion assumption is violated in common situations involving transparency, depth discontinuities, independently moving objects, shadows, and specular reflections. To robustly estimate optical flow, the single motion assumption must be relaxed. This paper presents a framework based on robust estimation that addresses violations of the brightness constancy and spatial smoothness assumptions caused by multiple motions. We show how the robust estimation framework can be applied to standard formulations of the optical flow problem thus reducing their sensitivity to violations of their underlying assumptions. The approach has been applied to three standard techniques for recovering optical flow: area-based regression, correlation, and regularization with motion discontinuities. This paper focuses on the recovery of multiple parametric motion models within a region, as well as the recovery of piecewise-smooth flow fields, and provides examples with natural and synthetic image sequences.

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pdf pdf from publisher [BibTex]

pdf pdf from publisher [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)

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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)

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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)

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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)

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pdf on-line at USPTO [BibTex]

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.

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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)

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abstract [BibTex]

abstract [BibTex]

1993


Mixture models for optical flow computation
Mixture models for optical flow computation

Jepson, A., Black, M.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-93, pages: 760-761, New York, NY, June 1993 (inproceedings)

Abstract
The computation of optical flow relies on merging information available over an image patch to form an estimate of 2-D image velocity at a point. This merging process raises many issues. These include the treatment of outliers in component velocity measurements and the modeling of multiple motions within a patch which arise from occlusion boundaries or transparency. A new approach for dealing with these issues is presented. It is based on the use of a probabilistic mixture model to explicitly represent multiple motions within a patch. A simple extension of the EM-algorithm is used to compute a maximum likelihood estimate for the various motion parameters. Preliminary experiments indicate that this approach is computationally efficient, and that it can provide robust estimates of the optical flow values in the presence of outliers and multiple motions.

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pdf tech report [BibTex]

1993


pdf tech report [BibTex]


A framework for the robust estimation of optical flow
A framework for the robust estimation of optical flow

(Helmholtz Prize)

Black, M. J., Anandan, P.

In Fourth International Conf. on Computer Vision, ICCV-93, pages: 231-236, Berlin, Germany, May 1993 (inproceedings)

Abstract
Most approaches for estimating optical flow assume that, within a finite image region, only a single motion is present. This single motion assumption is violated in common situations involving transparency, depth discontinuities, independently moving objects, shadows, and specular reflections. To robustly estimate optical flow, the single motion assumption must be relaxed. This work describes a framework based on robust estimation that addresses violations of the brightness constancy and spatial smoothness assumptions caused by multiple motions. We show how the robust estimation framework can be applied to standard formulations of the optical flow problem thus reducing their sensitivity to violations of their underlying assumptions. The approach has been applied to three standard techniques for recovering optical flow: area-based regression, correlation, and regularization with motion discontinuities. This work focuses on the recovery of multiple parametric motion models within a region as well as the recovery of piecewise-smooth flow fields and provides examples with natural and synthetic image sequences.

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pdf video abstract code [BibTex]

pdf video abstract code [BibTex]


Mixture models for optical flow computation
Mixture models for optical flow computation

Jepson, A., Black, M.

In Partitioning Data Sets, DIMACS Workshop, pages: 271-286, (Editors: Ingemar Cox, Pierre Hansen, and Bela Julesz), AMS Pub, Providence, RI., April 1993 (incollection)

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pdf [BibTex]

pdf [BibTex]


Action, representation, and purpose: Re-evaluating the foundations of computational vision
Action, representation, and purpose: Re-evaluating the foundations of computational vision

Black, M. J., Aloimonos, Y., Brown, C. M., Horswill, I., Malik, J., G. Sandini, , Tarr, M. J.

In International Joint Conference on Artificial Intelligence, IJCAI-93, pages: 1661-1666, Chambery, France, 1993 (inproceedings)

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pdf [BibTex]

pdf [BibTex]

1991


Dynamic motion estimation and feature extraction over long image sequences
Dynamic motion estimation and feature extraction over long image sequences

Black, M. J., Anandan, P.

In Proc. IJCAI Workshop on Dynamic Scene Understanding, Sydney, Australia, August 1991 (inproceedings)

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[BibTex]

1991


[BibTex]


Robust dynamic motion estimation over time
Robust dynamic motion estimation over time

(IEEE Computer Society Outstanding Paper Award)

Black, M. J., Anandan, P.

In Proc. Computer Vision and Pattern Recognition, CVPR-91,, pages: 296-302, Maui, Hawaii, June 1991 (inproceedings)

Abstract
This paper presents a novel approach to incrementally estimating visual motion over a sequence of images. We start by formulating constraints on image motion to account for the possibility of multiple motions. This is achieved by exploiting the notions of weak continuity and robust statistics in the formulation of the minimization problem. The resulting objective function is non-convex. Traditional stochastic relaxation techniques for minimizing such functions prove inappropriate for the task. We present a highly parallel incremental stochastic minimization algorithm which has a number of advantages over previous approaches. The incremental nature of the scheme makes it truly dynamic and permits the detection of occlusion and disocclusion boundaries.

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pdf video abstract [BibTex]

pdf video abstract [BibTex]

1990


A model for the detection of motion over time
A model for the detection of motion over time

Black, M. J., Anandan, P.

In Proc. Int. Conf. on Computer Vision, ICCV-90, pages: 33-37, Osaka, Japan, December 1990 (inproceedings)

Abstract
We propose a model for the recovery of visual motion fields from image sequences. Our model exploits three constraints on the motion of a patch in the environment: i) Data Conservation: the intensity structure corresponding to an environmental surface patch changes gradually over time; ii) Spatial Coherence: since surfaces have spatial extent neighboring points have similar motions; iii) Temporal Coherence: the direction and velocity of motion for a surface patch changes gradually. The formulation of the constraints takes into account the possibility of multiple motions at a particular location. We also present a highly parallel computational model for realizing these constraints in which computation occurs locally, knowledge about the motion increases over time, and occlusion and disocclusion boundaries are estimated. An implementation of the model using a stochastic temporal updating scheme is described. Experiments with both synthetic and real imagery are presented.

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pdf [BibTex]

1990


pdf [BibTex]


Constraints for the early detection of discontinuity from motion
Constraints for the early detection of discontinuity from motion

Black, M. J., Anandan, P.

In Proc. National Conf. on Artificial Intelligence, AAAI-90, pages: 1060-1066, Boston, MA, 1990 (inproceedings)

Abstract
Surface discontinuities are detected in a sequence of images by exploiting physical constraints at early stages in the processing of visual motion. To achieve accurate early discontinuity detection we exploit five physical constraints on the presence of discontinuities: i) the shape of the sum of squared differences (SSD) error surface in the presence of surface discontinuities; ii) the change in the shape of the SSD surface due to relative surface motion; iii) distribution of optic flow in a neighborhood of a discontinuity; iv) spatial consistency of discontinuities; V) temporal consistency of discontinuities. The constraints are described, and experimental results on sequences of real and synthetic images are presented. The work has applications in the recovery of environmental structure from motion and in the generation of dense optic flow fields.

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pdf [BibTex]

pdf [BibTex]