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2001


Thumb xl bildschirmfoto 2012 12 11 um 10.41.35
Dynamic coupled component analysis

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

In IEEE Proc. Computer Vision and Pattern Recognition, CVPR’01, 2, pages: 643-650, IEEE, Kauai, Hawaii, December 2001 (inproceedings)

pdf [BibTex]

2001

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 11.56.46
Robust principal component analysis for computer vision

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

In Int. Conf. on Computer Vision, ICCV-2001, II, pages: 362-369, Vancouver, BC, USA, 2001 (inproceedings)

pdf Project Page [BibTex]

pdf Project Page [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 10.58.16
Learning image statistics for Bayesian tracking

Sidenbladh, H., Black, M. J.

In Int. Conf. on Computer Vision, ICCV-2001, II, pages: 709-716, Vancouver, BC, USA, 2001 (inproceedings)

pdf [BibTex]

pdf [BibTex]


no image
Encoding/decoding of arm kinematics from simultaneously recorded MI neurons

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

Society for Neuroscience Abst. Vol. 27, Program No. 572.14, 2001 (conference)

abstract [BibTex]

abstract [BibTex]


Thumb xl bildschirmfoto 2012 12 11 um 12.05.35
Learning and tracking cyclic human motion

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

In Advances in Neural Information Processing Systems 13, NIPS, pages: 894-900, (Editors: Leen, Todd K. and Dietterich, Thomas G. and Tresp, Volker), The MIT Press, 2001 (inproceedings)

pdf [BibTex]

pdf [BibTex]

1999


Thumb xl bildschirmfoto 2013 01 14 um 09.07.06
Edges as outliers: Anisotropic smoothing using local image statistics

Black, M. J., Sapiro, G.

In Scale-Space Theories in Computer Vision, Second Int. Conf., Scale-Space ’99, pages: 259-270, LNCS 1682, Springer, Corfu, Greece, September 1999 (inproceedings)

Abstract
Edges are viewed as statistical outliers with respect to local image gradient magnitudes. Within local image regions we compute a robust statistical measure of the gradient variation and use this in an anisotropic diffusion framework to determine a spatially varying "edge-stopping" parameter σ. We show how to determine this parameter for two edge-stopping functions described in the literature (Perona-Malik and the Tukey biweight). Smoothing of the image is related the local texture and in regions of low texture, small gradient values may be treated as edges whereas in regions of high texture, large gradient magnitudes are necessary before an edge is preserved. Intuitively these results have similarities with human perceptual phenomena such as masking and "popout". Results are shown on a variety of standard images.

pdf [BibTex]

1999

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 07 um 12.35.15
Probabilistic detection and tracking of motion discontinuities

(Marr Prize, Honorable Mention)

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

In Int. Conf. on Computer Vision, ICCV-99, pages: 551-558, ICCV, Corfu, Greece, September 1999 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl paircover
Artscience Sciencart

Black, M. J., Levy, D., PamelaZ,

In Art and Innovation: The Xerox PARC Artist-in-Residence Program, pages: 244-300, (Editors: Harris, C.), MIT-Press, 1999 (incollection)

Abstract
One of the effects of the PARC Artist In Residence (PAIR) program has been to expose the strong connections between scientists and artists. Both do what they do because they need to do it. They are often called upon to justify their work in order to be allowed to continue to do it. They need to justify it to funders, to sponsoring institutions, corporations, the government, the public. They publish papers, teach workshops, and write grants touting the educational or health benefits of what they do. All of these things are to some extent valid, but the fact of the matter is: artists and scientists do their work because they are driven to do it. They need to explore and create.

This chapter attempts to give a flavor of one multi-way "PAIRing" between performance artist PamelaZ and two PARC researchers, Michael Black and David Levy. The three of us paired up because we found each other interesting. We chose each other. While most artists in the program are paired with a single researcher Pamela jokingly calls herself a bigamist for choosing two PAIR "husbands" with different backgrounds and interests.

There are no "rules" to the PAIR program; no one told us what to do with our time. Despite this we all had a sense that we needed to produce something tangible during Pamela's year-long residency. In fact, Pamela kept extending her residency because she did not feel as though we had actually made anything concrete. The interesting thing was that all along we were having great conversations, some of which Pamela recorded. What we did not see at the time was that it was these conversations between artists and scientists that are at the heart of the PAIR program and that these conversations were changing the way we thought about our own work and the relationships between science and art.

To give these conversations their due, and to allow the reader into our PAIR interactions, we include two of our many conversations in this chapter.

[BibTex]

[BibTex]


Thumb xl bildschirmfoto 2012 12 06 um 09.38.15
Parameterized modeling and recognition of activities

Yacoob, Y., Black, M. J.

Computer Vision and Image Understanding, 73(2):232-247, 1999 (article)

Abstract
In this paper we consider a class of human activities—atomic activities—which can be represented as a set of measurements over a finite temporal window (e.g., the motion of human body parts during a walking cycle) and which has a relatively small space of variations in performance. A new approach for modeling and recognition of atomic activities that employs principal component analysis and analytical global transformations is proposed. The modeling of sets of exemplar instances of activities that are similar in duration and involve similar body part motions is achieved by parameterizing their representation using principal component analysis. The recognition of variants of modeled activities is achieved by searching the space of admissible parameterized transformations that these activities can undergo. This formulation iteratively refines the recognition of the class to which the observed activity belongs and the transformation parameters that relate it to the model in its class. We provide several experiments on recognition of articulated and deformable human motions from image motion parameters.

pdf pdf from publisher DOI [BibTex]

pdf pdf from publisher DOI [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.12.47
Explaining optical flow events with parameterized spatio-temporal models

Black, M. J.

In IEEE Proc. Computer Vision and Pattern Recognition, CVPR’99, pages: 326-332, IEEE, Fort Collins, CO, 1999 (inproceedings)

pdf video [BibTex]

pdf video [BibTex]

1998


Thumb xl bildschirmfoto 2012 12 06 um 10.05.20
Summarization of video-taped presentations: Automatic analysis of motion and gesture

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

IEEE Trans. on Circuits and Systems for Video Technology, 8(5):686-696, September 1998 (article)

Abstract
This paper presents 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 set of actions that can be recognized based on the active contour shape and motion. The recognized actions provide an annotation of the sequence that can be used to access a condensed version of the talk from a Web page.

pdf pdf from publisher DOI [BibTex]

1998

pdf pdf from publisher DOI [BibTex]


Thumb xl bildschirmfoto 2012 12 06 um 12.22.18
Robust anisotropic diffusion

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

IEEE Transactions on Image Processing, 7(3):421-432, March 1998 (article)

Abstract
Relations between anisotropic diffusion and robust statistics are described in this paper. Specifically, 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 an image that has been smoothed with anisotropic diffusion. Additionally, we derive a relationship between anisotropic diffusion and regularization with line processes. Adding constraints on the spatial organization of the line processes allows us to develop new anisotropic diffusion equations that result in a qualitative improvement in the continuity of edges

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.33.36
The Digital Office: Overview

Black, M., Berard, F., Jepson, A., Newman, W., Saund, E., Socher, G., Taylor, M.

In AAAI Spring Symposium on Intelligent Environments, pages: 1-6, Stanford, March 1998 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.46.31
A framework for modeling appearance change in image sequences

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

In Sixth International Conf. on Computer Vision, ICCV’98, pages: 660-667, Mumbai, India, January 1998 (inproceedings)

Abstract
Image "appearance" may change over time due to a variety of causes such as 1) object or camera motion; 2) generic photometric events including variations in illumination (e.g. shadows) and specular reflections; and 3) "iconic changes" which are specific to the objects being viewed and include complex occlusion events and changes in the material properties of the objects. We propose a general framework for representing and recovering these "appearance changes" in an image sequence as a "mixture" of different causes. The approach generalizes previous work on optical flow to provide a richer description of image events and more reliable estimates of image motion.

pdf video [BibTex]

pdf video [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.49.49
Parameterized modeling and recognition of activities

Yacoob, Y., Black, M. J.

In Sixth International Conf. on Computer Vision, ICCV’98, pages: 120-127, Mumbai, India, January 1998 (inproceedings)

Abstract
A framework for modeling and recognition of temporal activities is proposed. The modeling of sets of exemplar activities is achieved by parameterizing their representation in the form of principal components. Recognition of spatio-temporal variants of modeled activities is achieved by parameterizing the search in the space of admissible transformations that the activities can undergo. Experiments on recognition of articulated and deformable object motion from image motion parameters are presented.

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.23.21
Motion feature detection using steerable flow fields

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

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-98, pages: 274-281, IEEE, Santa Barbara, CA, 1998 (inproceedings)

Abstract
The estimation and detection of occlusion boundaries and moving bars are important and challenging problems in image sequence analysis. Here, we model such motion features as linear combinations of steerable basis flow fields. These models constrain the interpretation of image motion, and are used in the same way as translational or affine motion models. We estimate the subspace coefficients of the motion feature models directly from spatiotemporal image derivatives using a robust regression method. From the subspace coefficients we detect the presence of a motion feature and solve for the orientation of the feature and the relative velocities of the surfaces. Our method does not require the prior computation of optical flow and recovers accurate estimates of orientation and velocity.

pdf [BibTex]

pdf [BibTex]


Thumb xl paybotteaser
PLAYBOT: A visually-guided robot for physically disabled children

Tsotsos, J. K., Verghese, G., Dickinson, S., Jenkin, M., Jepson, A., Milios, E., Nuflo, F., Stevenson, S., Black, M., Metaxas, D., Culhane, S., Ye, Y., Mann, R.

Image & Vision Computing, Special Issue on Vision for the Disabled, 16(4):275-292, 1998 (article)

Abstract
This paper overviews the PLAYBOT project, a long-term, large-scale research program whose goal is to provide a directable robot which may enable physically disabled children to access and manipulate toys. This domain is the first test domain, but there is nothing inherent in the design of PLAYBOT that prohibits its extension to other tasks. The research is guided by several important goals: vision is the primary sensor; vision is task directed; the robot must be able to visually search its environment; object and event recognition are basic capabilities; environments must be natural and dynamic; users and environments are assumed to be unpredictable; task direction and reactivity must be smoothly integrated; and safety is of high importance. The emphasis of the research has been on vision for the robot this is the most challenging research aspect and the major bottleneck to the development of intelligent robots. Since the control framework is behavior-based, the visual capabilities of PLAYBOT are described in terms of visual behaviors. Many of the components of PLAYBOT are briefly described and several examples of implemented sub-systems are shown. The paper concludes with a description of the current overall system implementation, and a complete example of PLAYBOT performing a simple task.

pdf pdf from publisher DOI [BibTex]

pdf pdf from publisher DOI [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.18.33
Visual surveillance of human activity

L. Davis, S. F., Harwood, D., Yacoob, Y., Hariatoglu, I., Black, M.

In Asian Conference on Computer Vision, ACCV, 1998 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.29.19
A Probabilistic framework for matching temporal trajectories: Condensation-based recognition of gestures and expressions

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

In European Conf. on Computer Vision, ECCV-98, pages: 909-924, Freiburg, Germany, 1998 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2012 12 06 um 12.33.38
EigenTracking: Robust matching and tracking of articulated objects using a view-based representation

Black, M. J., Jepson, A.

International Journal of Computer Vision, 26(1):63-84, 1998 (article)

Abstract
This paper describes an approach for tracking rigid and articulated objects using a view-based representation. The approach builds on and extends work on eigenspace representations, robust estimation techniques, and parameterized optical flow estimation. First, we note that the least-squares image reconstruction of standard eigenspace techniques has a number of problems and we reformulate the reconstruction problem as one of robust estimation. Second we define a “subspace constancy assumption” that allows us to exploit techniques for parameterized optical flow estimation to simultaneously solve for the view of an object and the affine transformation between the eigenspace and the image. To account for large affine transformations between the eigenspace and the image we define a multi-scale eigenspace representation and a coarse-to-fine matching strategy. Finally, we use these techniques to track objects over long image sequences in which the objects simultaneously undergo both affine image motions and changes of view. In particular we use this “EigenTracking” technique to track and recognize the gestures of a moving hand.

pdf pdf from publisher video [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 09.40.25
Recognizing temporal trajectories using the Condensation algorithm

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

In Int. Conf. on Automatic Face and Gesture Recognition, pages: 16-21, Nara, Japan, 1998 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl cipollabook
Looking at people in action - An overview

Yacoob, Y., Davis, L. S., Black, M., Gavrila, D., Horprasert, T., Morimoto, C.

In Computer Vision for Human–Machine Interaction, (Editors: R. Cipolla and A. Pentland), Cambridge University Press, 1998 (incollection)

publisher site google books [BibTex]

publisher site google books [BibTex]


Thumb xl bildschirmfoto 2013 01 14 um 10.58.31
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]


no image
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]


Thumb xl bildschirmfoto 2013 01 14 um 11.06.54
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]


Thumb xl patentc
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]


Thumb xl bildschirmfoto 2013 01 14 um 11.24.02
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]


no image
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]