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22 results (View BibTeX file of all listed publications)

2000

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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

Black, M. J., Fleet, D. J. Probabilistic detection and tracking of motion boundaries Int. J. of Computer Vision, 38(3):231-245, July 2000 (article)

pdf pdf from publisher Video [BibTex]

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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]

Sidenbladh, H., Black, M. J., Fleet, D. Stochastic tracking of 3D human figures using 2D image motion In European Conference on Computer Vision, ECCV, pages: 702-718, LNCS 1843, Springer Verlag, Dublin, Ireland, June 2000 (inproceedings)

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]

Ormoneit, D., Hastie, T., Black, M. J. Functional analysis of human motion data 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]

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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]

Ormoneit, D., Sidenbladh, H., Black, M. J., Hastie, T. Stochastic modeling and tracking of human motion Learning 2000, Snowbird, UT, April 2000 (conference)

abstract [BibTex]

Thumb xl bildschirmfoto 2012 12 12 um 11.40.47
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]

Sidenbladh, H., De la Torre, F., Black, M. J. A framework for modeling the appearance of 3D articulated figures In Int. Conf. on Automatic Face and Gesture Recognition, pages: 368-375, Grenoble, France, March 2000 (inproceedings)

pdf [BibTex]

Thumb xl bildschirmfoto 2012 12 06 um 09.22.34
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]

Fleet, D. J., Black, M. J., Yacoob, Y., Jepson, A. D. Design and use of linear models for image motion analysis Int. J. of Computer Vision, 36(3):171-193, 2000 (article)

pdf [BibTex]

Thumb xl bildschirmfoto 2012 12 06 um 09.48.16
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]

Black, M. J., Fleet, D. J., Yacoob, Y. Robustly estimating changes in image appearance Computer Vision and Image Understanding, 78(1):8-31, 2000 (article)

pdf pdf from publisher DOI [BibTex]

1997

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Robust anisotropic diffusion and sharpening of scalar and vector images

Black, M. J., Sapiro, G., Marimont, D., Heeger, D.

In Int. Conf. on Image Processing, ICIP, 1, pages: 263-266, Vol. 1, Santa Barbara, CA, October 1997 (inproceedings)

Abstract
Relations between anisotropic diffusion and robust statistics are described. We show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edge-stopping" function in the anisotropic diffusion equation is closely related to the error norm and influence function in the robust estimation framework. This connection leads to a new "edge-stopping" function based on Tukey's biweight robust estimator, that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. The robust statistical interpretation also provides a means for detecting the boundaries (edges) between the piecewise smooth regions in the image. We extend the framework to vector-valued images and show applications to robust image sharpening.

pdf publisher site [BibTex]

1997

Black, M. J., Sapiro, G., Marimont, D., Heeger, D. Robust anisotropic diffusion and sharpening of scalar and vector images In Int. Conf. on Image Processing, ICIP, 1, pages: 263-266, Vol. 1, Santa Barbara, CA, October 1997 (inproceedings)

pdf publisher site [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 10.31.38
Robust anisotropic diffusion: Connections between robust statistics, line processing, and anisotropic diffusion

Black, M. J., Sapiro, G., Marimont, D., Heeger, D.

In Scale-Space Theory in Computer Vision, Scale-Space’97, pages: 323-326, LNCS 1252, Springer Verlag, Utrecht, the Netherlands, July 1997 (inproceedings)

pdf [BibTex]

Black, M. J., Sapiro, G., Marimont, D., Heeger, D. Robust anisotropic diffusion: Connections between robust statistics, line processing, and anisotropic diffusion In Scale-Space Theory in Computer Vision, Scale-Space’97, pages: 323-326, LNCS 1252, Springer Verlag, Utrecht, the Netherlands, July 1997 (inproceedings)

pdf [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 10.05.56
Learning parameterized models of image motion

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

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-97, pages: 561-567, Puerto Rico, June 1997 (inproceedings)

Abstract
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that are computed from a training set using principal component analysis. Many complex image motions can be represented by a linear combination of a small number of these basis flows. The learned motion models may be used for optical flow estimation and for model-based recognition. For optical flow estimation we describe a robust, multi-resolution scheme for directly computing the parameters of the learned flow models from image derivatives. As examples we consider learning motion discontinuities, non-rigid motion of human mouths, and articulated human motion.

pdf [BibTex]

Black, M. J., Yacoob, Y., Jepson, A. D., Fleet, D. J. Learning parameterized models of image motion In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-97, pages: 561-567, Puerto Rico, June 1997 (inproceedings)

pdf [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 10.13.51
Analysis of gesture and action in technical talks for video indexing

Ju, S. X., Black, M. J., Minneman, S., Kimber, D.

In IEEE Conf. on Computer Vision and Pattern Recognition, pages: 595-601, CVPR-97, Puerto Rico, June 1997 (inproceedings)

Abstract
In this paper, we present an automatic system for analyzing and annotating video sequences of technical talks. Our method uses a robust motion estimation technique to detect key frames and segment the video sequence into subsequences containing a single overhead slide. The subsequences are stabilized to remove motion that occurs when the speaker adjusts their slides. Any changes remaining between frames in the stabilized sequences may be due to speaker gestures such as pointing or writing and we use active contours to automatically track these potential gestures. Given the constrained domain we define a simple ``vocabulary'' of actions which can easily be recognized based on the active contour shape and motion. The recognized actions provide a rich annotation of the sequence that can be used to access a condensed version of the talk from a web page.

pdf [BibTex]

Ju, S. X., Black, M. J., Minneman, S., Kimber, D. Analysis of gesture and action in technical talks for video indexing In IEEE Conf. on Computer Vision and Pattern Recognition, pages: 595-601, CVPR-97, Puerto Rico, June 1997 (inproceedings)

pdf [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 10.36.36
Modeling appearance change in image sequences

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

In Advances in Visual Form Analysis, pages: 11-20, Proceedings of the Third International Workshop on Visual Form, Capri, Italy, May 1997 (inproceedings)

abstract [BibTex]

Black, M. J., Yacoob, Y., Fleet, D. J. Modeling appearance change in image sequences In Advances in Visual Form Analysis, pages: 11-20, Proceedings of the Third International Workshop on Visual Form, Capri, Italy, May 1997 (inproceedings)

abstract [BibTex]

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Recognizing facial expressions in image sequences using local parameterized models of image motion

Black, M. J., Yacoob, Y.

Int. Journal of Computer Vision, 25(1):23-48, 1997 (article)

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 performed with high accuracy in extensive laboratory experiments involving 40 subjects as well as in television and movie sequences.

pdf pdf from publisher abstract video [BibTex]

Thumb xl bildschirmfoto 2013 01 15 um 11.00.33
Recognizing human motion using parameterized models of optical flow

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

In Motion-Based Recognition, pages: 245-269, (Editors: Mubarak Shah and Ramesh Jain,), Kluwer Academic Publishers, Boston, MA, 1997 (incollection)

pdf [BibTex]

Black, M. J., Yacoob, Y., Ju, X. S. Recognizing human motion using parameterized models of optical flow In Motion-Based Recognition, pages: 245-269, (Editors: Mubarak Shah and Ramesh Jain,), Kluwer Academic Publishers, Boston, MA, 1997 (incollection)

pdf [BibTex]

1994

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Estimating multiple independent motions in segmented images using parametric models with local deformations

Black, M. J., Jepson, A.

In Workshop on Non-rigid and Articulate Motion, pages: 220-227, Austin, Texas, November 1994 (inproceedings)

pdf abstract [BibTex]

1994

Black, M. J., Jepson, A. Estimating multiple independent motions in segmented images using parametric models with local deformations In Workshop on Non-rigid and Articulate Motion, pages: 220-227, Austin, Texas, November 1994 (inproceedings)

pdf abstract [BibTex]

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Time to contact from active tracking of motion boundaries

Ju, X., Black, M. J.

In Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, pages: 26-37, Proc. SPIE 2354, Boston, Massachusetts, November 1994 (inproceedings)

pdf abstract [BibTex]

Ju, X., Black, M. J. Time to contact from active tracking of motion boundaries In Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, pages: 26-37, Proc. SPIE 2354, Boston, Massachusetts, November 1994 (inproceedings)

pdf abstract [BibTex]

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A computational and evolutionary perspective on the role of representation in computer vision

Tarr, M. J., Black, M. J.

CVGIP: Image Understanding, 60(1):65-73, July 1994 (article)

Abstract
Recently, the assumed goal of computer vision, reconstructing a representation of the scene, has been critcized as unproductive and impractical. Critics have suggested that the reconstructive approach should be supplanted by a new purposive approach that emphasizes functionality and task driven perception at the cost of general vision. In response to these arguments, we claim that the recovery paradigm central to the reconstructive approach is viable, and, moreover, provides a promising framework for understanding and modeling general purpose vision in humans and machines. An examination of the goals of vision from an evolutionary perspective and a case study involving the recovery of optic flow support this hypothesis. In particular, while we acknowledge that there are instances where the purposive approach may be appropriate, these are insufficient for implementing the wide range of visual tasks exhibited by humans (the kind of flexible vision system presumed to be an end-goal of artificial intelligence). Furthermore, there are instances, such as recent work on the estimation of optic flow, where the recovery paradigm may yield useful and robust results. Thus, contrary to certain claims, the purposive approach does not obviate the need for recovery and reconstruction of flexible representations of the world.

pdf [BibTex]

Tarr, M. J., Black, M. J. A computational and evolutionary perspective on the role of representation in computer vision CVGIP: Image Understanding, 60(1):65-73, July 1994 (article)

pdf [BibTex]

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Reconstruction and purpose

Tarr, M. J., Black, M. J.

CVGIP: Image Understanding, 60(1):113-118, July 1994 (article)

pdf [BibTex]

Tarr, M. J., Black, M. J. Reconstruction and purpose CVGIP: Image Understanding, 60(1):113-118, July 1994 (article)

pdf [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 11.39.54
The outlier process: Unifying line processes and robust statistics

Black, M., Rangarajan, A.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR’94, pages: 15-22, Seattle, WA, June 1994 (inproceedings)

pdf abstract [BibTex]

Black, M., Rangarajan, A. The outlier process: Unifying line processes and robust statistics In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR’94, pages: 15-22, Seattle, WA, June 1994 (inproceedings)

pdf abstract [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 11.42.57
Recursive non-linear estimation of discontinuous flow fields

Black, M.

In Proc. Third European Conf. on Computer Vision, ECCV’94,, pages: 138-145, LNCS 800, Springer Verlag, Sweden, May 1994 (inproceedings)

pdf abstract [BibTex]

Black, M. Recursive non-linear estimation of discontinuous flow fields In Proc. Third European Conf. on Computer Vision, ECCV’94,, pages: 138-145, LNCS 800, Springer Verlag, Sweden, May 1994 (inproceedings)

pdf abstract [BibTex]

1990

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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.

pdf [BibTex]

1990

Black, M. J., Anandan, P. A model for the detection of motion over time In Proc. Int. Conf. on Computer Vision, ICCV-90, pages: 33-37, Osaka, Japan, December 1990 (inproceedings)

pdf [BibTex]

Thumb xl bildschirmfoto 2013 01 14 um 12.14.18
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.

pdf [BibTex]

Black, M. J., Anandan, P. Constraints for the early detection of discontinuity from motion In Proc. National Conf. on Artificial Intelligence, AAAI-90, pages: 1060-1066, Boston, MA, 1990 (inproceedings)

pdf [BibTex]