Publications | Perceiving Systems - Max Planck Institute for Intelligent Systems

43 results (View BibTeX file of all listed publications)

2007

A Database and Evaluation Methodology for Optical Flow

Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.

In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

2007

Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R. A Database and Evaluation Methodology for Optical Flow In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf [BibTex]

Shining a light on human pose: On shadows, shading and the estimation of pose and shape,

Balan, A., Black, M. J., Haussecker, H., Sigal, L.

In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf YouTube [BibTex]

Balan, A., Black, M. J., Haussecker, H., Sigal, L. Shining a light on human pose: On shadows, shading and the estimation of pose and shape, In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, October 2007 (inproceedings)

pdf YouTube [BibTex]

Ensemble spiking activity as a source of cortical control signals in individuals with tetraplegia

Simeral, J. D., Kim, S. P., Black, M. J., Donoghue, J. P., Hochberg, L. R.

Biomedical Engineering Society, BMES, september 2007 (conference)

[BibTex]

Simeral, J. D., Kim, S. P., Black, M. J., Donoghue, J. P., Hochberg, L. R. Ensemble spiking activity as a source of cortical control signals in individuals with tetraplegia Biomedical Engineering Society, BMES, september 2007 (conference)

[BibTex]

Detailed human shape and pose from images

Balan, A., Sigal, L., Black, M. J., Davis, J., Haussecker, H.

In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, pages: 1-8, Minneapolis, June 2007 (inproceedings)

pdf YouTube [BibTex]

Balan, A., Sigal, L., Black, M. J., Davis, J., Haussecker, H. Detailed human shape and pose from images In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, pages: 1-8, Minneapolis, June 2007 (inproceedings)

pdf YouTube [BibTex]

Learning static Gestalt laws through dynamic experience

Ostrovsky, Y., Wulff, J., Sinha, P.

Journal of Vision, 7(9):315-315, ARVO, June 2007 (article)

Abstract

The Gestalt laws (Wertheimer 1923) are widely regarded as the rules that help us parse the world into objects. However, it is unclear as to how these laws are acquired by an infant's visual system. Classically, these “laws” have been presumed to be innate (Kellman and Spelke 1983). But, more recent work in infant development, showing the protracted time-course over which these grouping principles emerge (e.g., Johnson and Aslin 1995; Craton 1996), suggests that visual experience might play a role in their genesis. Specifically, our studies of patients with late-onset vision (Project Prakash; VSS 2006) and evidence from infant development both point to an early role of common motion cues for object grouping. Here we explore the possibility that the privileged status of motion in the developmental timeline is not happenstance, but rather serves to bootstrap the learning of static Gestalt cues. Our approach involves computational analyses of real-world motion sequences to investigate whether primitive optic flow information is correlated with static figural cues that could eventually come to serve as proxies for grouping in the form of Gestalt principles. We calculated local optic flow maps and then examined how similarity of motion across image patches co-varied with similarity of certain figural properties in static frames. Results indicate that patches with similar motion are much more likely to have similar luminance, color, and orientation as compared to patches with dissimilar motion vectors. This regularity suggests that, in principle, common motion extracted from dynamic visual experience can provide enough information to bootstrap region grouping based on luminance and color and contour continuation mechanisms in static scenes. These observations, coupled with the cited experimental studies, lend credence to the hypothesis that static Gestalt laws might be learned through a bootstrapping process based on early dynamic experience.

link (url) DOI [BibTex]

Ostrovsky, Y., Wulff, J., Sinha, P. Learning static Gestalt laws through dynamic experience Journal of Vision, 7(9):315-315, ARVO, June 2007 (article)

link (url) DOI [BibTex]

Decoding grasp aperture from motor-cortical population activity

Artemiadis, P., Shakhnarovich, G., Vargas-Irwin, C., Donoghue, J. P., Black, M. J.

In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 518-521, May 2007 (inproceedings)

pdf [BibTex]

Artemiadis, P., Shakhnarovich, G., Vargas-Irwin, C., Donoghue, J. P., Black, M. J. Decoding grasp aperture from motor-cortical population activity In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 518-521, May 2007 (inproceedings)

pdf [BibTex]

Multi-state decoding of point-and-click control signals from motor cortical activity in a human with tetraplegia

Kim, S., Simeral, J., Hochberg, L., Donoghue, J. P., Friehs, G., Black, M. J.

In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 486-489, May 2007 (inproceedings)

Abstract

Basic neural-prosthetic control of a computer cursor has been recently demonstrated by Hochberg et al. [1] using the BrainGate system (Cyberkinetics Neurotechnology Systems, Inc.). While these results demonstrate the feasibility of intracortically-driven prostheses for humans with paralysis, a practical cursor-based computer interface requires more precise cursor control and the ability to “click” on areas of interest. Here we present a practical point and click device that decodes both continuous states (e.g. cursor kinematics) and discrete states (e.g. click state) from single neural population in human motor cortex. We describe a probabilistic multi-state decoder and the necessary training paradigms that enable point and click cursor control by a human with tetraplegia using an implanted microelectrode array. We present results from multiple recording sessions and quantify the point and click performance.

pdf [BibTex]

Kim, S., Simeral, J., Hochberg, L., Donoghue, J. P., Friehs, G., Black, M. J. Multi-state decoding of point-and-click control signals from motor cortical activity in a human with tetraplegia In The 3rd International IEEE EMBS Conference on Neural Engineering, pages: 486-489, May 2007 (inproceedings)

pdf [BibTex]

Neuromotor prosthesis development

Donoghue, J., Hochberg, L., Nurmikko, A., Black, M., Simeral, J., Friehs, G.

Medicine & Health Rhode Island, 90(1):12-15, January 2007 (article)

Abstract

Article describes a neuromotor prosthesis (NMP), in development at Brown University, that records human brain signals, decodes them, and transforms them into movement commands. An NMP is described as a system consisting of a neural interface, a decoding system, and a user interface, also called an effector; a closed-loop system would be completed by a feedback signal from the effector to the brain. The interface is based on neural spiking, a source of information-rich, rapid, complex control signals from the nervous system. The NMP described, named BrainGate, consists of a match-head sized platform with 100 thread-thin electrodes implanted just into the surface of the motor cortex where commands to move the hand emanate. Neural signals are decoded by a rack of computers that displays the resultant output as the motion of a cursor on a computer monitor. While computer cursor motion represents a form of virtual device control, this same command signal could be routed to a device to command motion of paralyzed muscles or the actions of prosthetic limbs. The researchers’ overall goal is the development of a fully implantable, wireless multi-neuron sensor for broad research, neural prosthetic, and human neurodiagnostic applications.

pdf [BibTex]

Donoghue, J., Hochberg, L., Nurmikko, A., Black, M., Simeral, J., Friehs, G. Neuromotor prosthesis development Medicine & Health Rhode Island, 90(1):12-15, January 2007 (article)

pdf [BibTex]

On the spatial statistics of optical flow

Roth, S., Black, M. J.

International Journal of Computer Vision, 74(1):33-50, 2007 (article)

Abstract

We present an analysis of the spatial and temporal statistics of "natural" optical flow fields and a novel flow algorithm that exploits their spatial statistics. Training flow fields are constructed using range images of natural scenes and 3D camera motions recovered from hand-held and car-mounted video sequences. A detailed analysis of optical flow statistics in natural scenes is presented and machine learning methods are developed to learn a Markov random field model of optical flow. The prior probability of a flow field is formulated as a Field-of-Experts model that captures the spatial statistics in overlapping patches and is trained using contrastive divergence. This new optical flow prior is compared with previous robust priors and is incorporated into a recent, accurate algorithm for dense optical flow computation. Experiments with natural and synthetic sequences illustrate how the learned optical flow prior quantitatively improves flow accuracy and how it captures the rich spatial structure found in natural scene motion.

pdf preprint pdf from publisher [BibTex]

Roth, S., Black, M. J. On the spatial statistics of optical flow International Journal of Computer Vision, 74(1):33-50, 2007 (article)

pdf preprint pdf from publisher [BibTex]

Deterministic Annealing for Multiple-Instance Learning

Gehler, P., Chapelle, O.

In Artificial Intelligence and Statistics (AIStats), 2007 (inproceedings)

pdf [BibTex]

Gehler, P., Chapelle, O. Deterministic Annealing for Multiple-Instance Learning In Artificial Intelligence and Statistics (AIStats), 2007 (inproceedings)

pdf [BibTex]

Point-and-click cursor control by a person with tetraplegia using an intracortical neural interface system

Kim, S., Simeral, J. D., Hochberg, L. R., Friehs, G., Donoghue, J. P., Black, M. J.

Program No. 517.2. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Kim, S., Simeral, J. D., Hochberg, L. R., Friehs, G., Donoghue, J. P., Black, M. J. Point-and-click cursor control by a person with tetraplegia using an intracortical neural interface system Program No. 517.2. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Assistive technology and robotic control using MI ensemble-based neural interface systems in humans with tetraplegia

Donoghue, J. P., Nurmikko, A., Black, M. J., Hochberg, L.

Journal of Physiology, Special Issue on Brain Computer Interfaces, 579, pages: 603-611, 2007 (article)

Abstract

This review describes the rationale, early stage development, and initial human application of neural interface systems (NISs) for humans with paralysis. NISs are emerging medical devices designed to allowpersonswith paralysis to operate assistive technologies or to reanimatemuscles based upon a command signal that is obtained directly fromthe brain. Such systems require the development of sensors to detect brain signals, decoders to transformneural activity signals into a useful command, and an interface for the user.We review initial pilot trial results of an NIS that is based on an intracortical microelectrode sensor that derives control signals from the motor cortex.We review recent findings showing, first, that neurons engaged by movement intentions persist in motor cortex years after injury or disease to the motor system, and second, that signals derived from motor cortex can be used by persons with paralysis to operate a range of devices. We suggest that, with further development, this form of NIS holds promise as a useful new neurotechnology for those with limited motor function or communication.We also discuss the additional potential for neural sensors to be used in the diagnosis and management of various neurological conditions and as a new way to learn about human brain function.

pdf preprint pdf from publisher DOI [BibTex]

Donoghue, J. P., Nurmikko, A., Black, M. J., Hochberg, L. Assistive technology and robotic control using MI ensemble-based neural interface systems in humans with tetraplegia Journal of Physiology, Special Issue on Brain Computer Interfaces, 579, pages: 603-611, 2007 (article)

pdf preprint pdf from publisher DOI [BibTex]

Probabilistically modeling and decoding neural population activity in motor cortex

Black, M. J., Donoghue, J. P.

In Toward Brain-Computer Interfacing, pages: 147-159, (Editors: Dornhege, G. and del R. Millan, J. and Hinterberger, T. and McFarland, D. and Muller, K.-R.), MIT Press, London, 2007 (incollection)

pdf [BibTex]

Black, M. J., Donoghue, J. P. Probabilistically modeling and decoding neural population activity in motor cortex In Toward Brain-Computer Interfacing, pages: 147-159, (Editors: Dornhege, G. and del R. Millan, J. and Hinterberger, T. and McFarland, D. and Muller, K.-R.), MIT Press, London, 2007 (incollection)

pdf [BibTex]

Learning Appearances with Low-Rank SVM

Wolf, L., Jhuang, H., Hazan, T.

In Conference on Computer Vision and Pattern Recognition (CVPR), 2007 (inproceedings)

pdf [BibTex]

Wolf, L., Jhuang, H., Hazan, T. Learning Appearances with Low-Rank SVM In Conference on Computer Vision and Pattern Recognition (CVPR), 2007 (inproceedings)

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Neural correlates of grip aperture in primary motor cortex

Vargas-Irwin, C., Shakhnarovich, G., Artemiadis, P., Donoghue, J. P., Black, M. J.

Program No. 517.10. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Vargas-Irwin, C., Shakhnarovich, G., Artemiadis, P., Donoghue, J. P., Black, M. J. Neural correlates of grip aperture in primary motor cortex Program No. 517.10. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Directional tuning in motor cortex of a person with ALS

Simeral, J. D., Donoghue, J. P., Black, M. J., Friehs, G. M., Brown, R. H., Krivickas, L. S., Hochberg, L. R.

Program No. 517.4. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Simeral, J. D., Donoghue, J. P., Black, M. J., Friehs, G. M., Brown, R. H., Krivickas, L. S., Hochberg, L. R. Directional tuning in motor cortex of a person with ALS Program No. 517.4. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Denoising archival films using a learned Bayesian model

Moldovan, T. M., Roth, S., Black, M. J.

(CS-07-03), Brown University, Department of Computer Science, 2007 (techreport)

pdf [BibTex]

Moldovan, T. M., Roth, S., Black, M. J. Denoising archival films using a learned Bayesian model (CS-07-03), Brown University, Department of Computer Science, 2007 (techreport)

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Steerable random fields

(Best Paper Award, INI-Graphics Net, 2008)

Roth, S., Black, M. J.

In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, 2007 (inproceedings)

pdf [BibTex]

Roth, S., Black, M. J. Steerable random fields In Int. Conf. on Computer Vision, ICCV, pages: 1-8, Rio de Janeiro, Brazil, 2007 (inproceedings)

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Toward standardized assessment of pointing devices for brain-computer interfaces

Donoghue, J., Simeral, J., Kim, S., G.M. Friehs, L. H., Black, M.

Program No. 517.16. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Donoghue, J., Simeral, J., Kim, S., G.M. Friehs, L. H., Black, M. Toward standardized assessment of pointing devices for brain-computer interfaces Program No. 517.16. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

A Biologically Inspired System for Action Recognition

Jhuang, H., Serre, T., Wolf, L., Poggio, T.

In International Conference on Computer Vision (ICCV), 2007 (inproceedings)

code pdf [BibTex]

Jhuang, H., Serre, T., Wolf, L., Poggio, T. A Biologically Inspired System for Action Recognition In International Conference on Computer Vision (ICCV), 2007 (inproceedings)

code pdf [BibTex]

AREADNE Research in Encoding And Decoding of Neural Ensembles

Shakhnarovich, G., Hochberg, L. R., Donoghue, J. P., Stein, J., Brown, R. H., Krivickas, L. S., Friehs, G. M., Black, M. J.

Program No. 517.8. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

Shakhnarovich, G., Hochberg, L. R., Donoghue, J. P., Stein, J., Brown, R. H., Krivickas, L. S., Friehs, G. M., Black, M. J. AREADNE Research in Encoding And Decoding of Neural Ensembles Program No. 517.8. 2007 Abstract Viewer and Itinerary Planner, Society for Neuroscience, San Diego, CA, 2007, Online (conference)

[BibTex]

2002

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

Wu, W., Black, M. J., Gao, Y., Bienenstock, E., Serruya, M., Donoghue, J. P. Inferring hand motion from multi-cell recordings in motor cortex using a Kalman filter 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]

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]

Fleet, D. J., Black, M. J., Nestares, O. Bayesian Inference of Visual Motion Boundaries In Exploring Artificial Intelligence in the New Millennium, pages: 139-174, (Editors: Lakemeyer, G. and Nebel, B.), Morgan Kaufmann Pub., July 2002 (incollection)

pdf [BibTex]

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]

Wu, W., Black M., Gao, Y., Bienenstock, E., Serruya, M., Donoghue, J. Inferring hand motion from multi-cell recordings in motor cortex using a Kalman filter Program No. 357.5. 2002 Abstract Viewer/Itinerary Planner, Society for Neuroscience, Washington, DC, 2002, Online (conference)

abstract [BibTex]

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]

Fablet, R., Black, M. J. Automatic detection and tracking of human motion with a view-based representation 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)

pdf [BibTex]

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]

Fleet, D. J., Jepson, A., Black, M. J. A layered motion representation with occlusion and compact spatial support 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)

pdf [BibTex]

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]

Sidenbladh, H., Black, M. J., Sigal, L. Implicit probabilistic models of human motion for synthesis and tracking In European Conf. on Computer Vision, 1, pages: 784-800, 2002 (inproceedings)

pdf [BibTex]

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]

De la Torre, F., Black, M. J. Robust parameterized component analysis: Theory and applications to 2D facial modeling In European Conf. on Computer Vision, ECCV 2002, 4, pages: 653-669, LNCS 2353, Springer-Verlag, 2002 (inproceedings)

pdf [BibTex]

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]

Gao, Y., Black, M. J., Bienenstock, E., Shoham, S., Donoghue, J. Probabilistic inference of hand motion from neural activity in motor cortex In Advances in Neural Information Processing Systems 14, pages: 221-228, MIT Press, 2002 (inproceedings)

pdf [BibTex]

2000

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]

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]

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]

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]

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]

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]

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]

1993

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)

pdf abstract tech report [BibTex]

1993

Jepson, A., Black, M. Mixture models for optical flow computation In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR-93, pages: 760-761, New York, NY, June 1993 (inproceedings)

pdf abstract tech report [BibTex]

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.

pdf video abstract code [BibTex]

Black, M. J., Anandan, P. A framework for the robust estimation of optical flow In Fourth International Conf. on Computer Vision, ICCV-93, pages: 231-236, Berlin, Germany, May 1993 (inproceedings)

pdf video abstract code [BibTex]

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)

pdf [BibTex]

Jepson, A., Black, M. Mixture models for optical flow computation In Partitioning Data Sets, DIMACS Workshop, pages: 271-286, (Editors: Ingemar Cox, Pierre Hansen, and Bela Julesz), AMS Pub, Providence, RI., April 1993 (incollection)

pdf [BibTex]

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)

pdf [BibTex]

Black, M. J., Aloimonos, Y., Brown, C. M., Horswill, I., Malik, J., G. Sandini, , Tarr, M. J. Action, representation, and purpose: Re-evaluating the foundations of computational vision In International Joint Conference on Artificial Intelligence, IJCAI-93, pages: 1661-1666, Chambery, France, 1993 (inproceedings)

pdf [BibTex]

1992

Psychophysical implications of temporal persistence in early vision: A computational account of representational momentum

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

Investigative Ophthalmology and Visual Science Supplement, Vol. 36, No. 4, 33, pages: 1050, May 1992 (conference)

abstract [BibTex]

1992

Tarr, M. J., Black, M. J. Psychophysical implications of temporal persistence in early vision: A computational account of representational momentum Investigative Ophthalmology and Visual Science Supplement, Vol. 36, No. 4, 33, pages: 1050, May 1992 (conference)

abstract [BibTex]

Combining intensity and motion for incremental segmentation and tracking over long image sequences

Black, M. J.

In Proc. Second European Conf. on Computer Vision, ECCV-92, pages: 485-493, LNCS 588, Springer Verlag, May 1992 (inproceedings)

pdf video abstract [BibTex]

Black, M. J. Combining intensity and motion for incremental segmentation and tracking over long image sequences In Proc. Second European Conf. on Computer Vision, ECCV-92, pages: 485-493, LNCS 588, Springer Verlag, May 1992 (inproceedings)

pdf video abstract [BibTex]

Robust Incremental Optical Flow

Black, M. J.

Yale University, Department of Computer Science, New Haven, CT, 1992, Research Report YALEU-DCS-RR-923 (phdthesis)

pdf code [BibTex]

Black, M. J. Robust Incremental Optical Flow Yale University, Department of Computer Science, New Haven, CT, 1992, Research Report YALEU-DCS-RR-923 (phdthesis)

pdf code [BibTex]

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