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35 results (View BibTeX file of all listed publications)

2006

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Finding directional movement representations in motor cortical neural populations using nonlinear manifold learning

WorKim, S., Simeral, J., Jenkins, O., Donoghue, J., Black, M.

World Congress on Medical Physics and Biomedical Engineering 2006, Seoul, Korea, August 2006 (conference)

[BibTex]

2006

WorKim, S., Simeral, J., Jenkins, O., Donoghue, J., Black, M. Finding directional movement representations in motor cortical neural populations using nonlinear manifold learning World Congress on Medical Physics and Biomedical Engineering 2006, Seoul, Korea, August 2006 (conference)

[BibTex]

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A non-parametric Bayesian approach to spike sorting

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

In International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pages: 1165-1169, New York, NY, August 2006 (inproceedings)

pdf [BibTex]

Wood, F., Goldwater, S., Black, M. J. A non-parametric Bayesian approach to spike sorting In International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pages: 1165-1169, New York, NY, August 2006 (inproceedings)

pdf [BibTex]

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Predicting 3D people from 2D pictures

(Best Paper)

Sigal, L., Black, M. J.

In Proc. IV Conf. on Articulated Motion and DeformableObjects (AMDO), LNCS 4069, pages: 185-195, July 2006 (inproceedings)

Abstract
We propose a hierarchical process for inferring the 3D pose of a person from monocular images. First we infer a learned view-based 2D body model from a single image using non-parametric belief propagation. This approach integrates information from bottom-up body-part proposal processes and deals with self-occlusion to compute distributions over limb poses. Then, we exploit a learned Mixture of Experts model to infer a distribution of 3D poses conditioned on 2D poses. This approach is more general than recent work on inferring 3D pose directly from silhouettes since the 2D body model provides a richer representation that includes the 2D joint angles and the poses of limbs that may be unobserved in the silhouette. We demonstrate the method in a laboratory setting where we evaluate the accuracy of the 3D poses against ground truth data. We also estimate 3D body pose in a monocular image sequence. The resulting 3D estimates are sufficiently accurate to serve as proposals for the Bayesian inference of 3D human motion over time

pdf pdf from publisher Video [BibTex]

Sigal, L., Black, M. J. Predicting 3D people from 2D pictures In Proc. IV Conf. on Articulated Motion and DeformableObjects (AMDO), LNCS 4069, pages: 185-195, July 2006 (inproceedings)

pdf pdf from publisher Video [BibTex]

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Specular flow and the recovery of surface structure

Roth, S., Black, M.

In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, 2, pages: 1869-1876, New York, NY, June 2006 (inproceedings)

Abstract
In scenes containing specular objects, the image motion observed by a moving camera may be an intermixed combination of optical flow resulting from diffuse reflectance (diffuse flow) and specular reflection (specular flow). Here, with few assumptions, we formalize the notion of specular flow, show how it relates to the 3D structure of the world, and develop an algorithm for estimating scene structure from 2D image motion. Unlike previous work on isolated specular highlights we use two image frames and estimate the semi-dense flow arising from the specular reflections of textured scenes. We parametrically model the image motion of a quadratic surface patch viewed from a moving camera. The flow is modeled as a probabilistic mixture of diffuse and specular components and the 3D shape is recovered using an Expectation-Maximization algorithm. Rather than treating specular reflections as noise to be removed or ignored, we show that the specular flow provides additional constraints on scene geometry that improve estimation of 3D structure when compared with reconstruction from diffuse flow alone. We demonstrate this for a set of synthetic and real sequences of mixed specular-diffuse objects.

pdf [BibTex]

Roth, S., Black, M. Specular flow and the recovery of surface structure In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, 2, pages: 1869-1876, New York, NY, June 2006 (inproceedings)

pdf [BibTex]

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An adaptive appearance model approach for model-based articulated object tracking

Balan, A., Black, M. J.

In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, 1, pages: 758-765, New York, NY, June 2006 (inproceedings)

Abstract
The detection and tracking of three-dimensional human body models has progressed rapidly but successful approaches typically rely on accurate foreground silhouettes obtained using background segmentation. There are many practical applications where such information is imprecise. Here we develop a new image likelihood function based on the visual appearance of the subject being tracked. We propose a robust, adaptive, appearance model based on the Wandering-Stable-Lost framework extended to the case of articulated body parts. The method models appearance using a mixture model that includes an adaptive template, frame-to-frame matching and an outlier process. We employ an annealed particle filtering algorithm for inference and take advantage of the 3D body model to predict self occlusion and improve pose estimation accuracy. Quantitative tracking results are presented for a walking sequence with a 180 degree turn, captured with four synchronized and calibrated cameras and containing significant appearance changes and self-occlusion in each view.

pdf [BibTex]

Balan, A., Black, M. J. An adaptive appearance model approach for model-based articulated object tracking In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, 1, pages: 758-765, New York, NY, June 2006 (inproceedings)

pdf [BibTex]

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Measure locally, reason globally: Occlusion-sensitive articulated pose estimation

Sigal, L., Black, M. J.

In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, 2, pages: 2041-2048, New York, NY, June 2006 (inproceedings)

pdf [BibTex]

Sigal, L., Black, M. J. Measure locally, reason globally: Occlusion-sensitive articulated pose estimation In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR, 2, pages: 2041-2048, New York, NY, June 2006 (inproceedings)

pdf [BibTex]

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Statistical analysis of the non-stationarity of neural population codes

Kim, S., Wood, F., Fellows, M., Donoghue, J. P., Black, M. J.

In BioRob 2006, The first IEEE / RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, pages: 295-299, Pisa, Italy, Febuary 2006 (inproceedings)

pdf [BibTex]

Kim, S., Wood, F., Fellows, M., Donoghue, J. P., Black, M. J. Statistical analysis of the non-stationarity of neural population codes In BioRob 2006, The first IEEE / RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, pages: 295-299, Pisa, Italy, Febuary 2006 (inproceedings)

pdf [BibTex]

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How to choose the covariance for Gaussian process regression independently of the basis

Franz, M., Gehler, P.

In Proceedings of the Workshop Gaussian Processes in Practice, 2006 (inproceedings)

pdf [BibTex]

Franz, M., Gehler, P. How to choose the covariance for Gaussian process regression independently of the basis In Proceedings of the Workshop Gaussian Processes in Practice, 2006 (inproceedings)

pdf [BibTex]

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The rate adapting poisson model for information retrieval and object recognition

Gehler, P. V., Holub, A. D., Welling, M.

In Proceedings of the 23rd international conference on Machine learning, pages: 337-344, ICML ’06, ACM, New York, NY, USA, 2006 (inproceedings)

project page pdf DOI [BibTex]

Gehler, P. V., Holub, A. D., Welling, M. The rate adapting poisson model for information retrieval and object recognition In Proceedings of the 23rd international conference on Machine learning, pages: 337-344, ICML ’06, ACM, New York, NY, USA, 2006 (inproceedings)

project page pdf DOI [BibTex]

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Implicit Wiener Series, Part II: Regularised estimation

Gehler, P., Franz, M.

(148), Max Planck Institute, 2006 (techreport)

pdf [BibTex]

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Tracking complex objects using graphical object models

Sigal, L., Zhu, Y., Comaniciu, D., Black, M. J.

In International Workshop on Complex Motion, LNCS 3417, pages: 223-234, Springer-Verlag, 2006 (inproceedings)

pdf pdf from publisher [BibTex]

Sigal, L., Zhu, Y., Comaniciu, D., Black, M. J. Tracking complex objects using graphical object models In International Workshop on Complex Motion, LNCS 3417, pages: 223-234, Springer-Verlag, 2006 (inproceedings)

pdf pdf from publisher [BibTex]

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HumanEva: Synchronized video and motion capture dataset for evaluation of articulated human motion

Sigal, L., Black, M. J.

(CS-06-08), Brown University, Department of Computer Science, 2006 (techreport)

pdf abstract [BibTex]

Sigal, L., Black, M. J. HumanEva: Synchronized video and motion capture dataset for evaluation of articulated human motion (CS-06-08), Brown University, Department of Computer Science, 2006 (techreport)

pdf abstract [BibTex]

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Bayesian population decoding of motor cortical activity using a Kalman filter

Wu, W., Gao, Y., Bienenstock, E., Donoghue, J. P., Black, M. J.

Neural Computation, 18(1):80-118, 2006 (article)

Abstract
Effective neural motor prostheses require a method for decoding neural activity representing desired movement. In particular, the accurate reconstruction of a continuous motion signal is necessary for the control of devices such as computer cursors, robots, or a patient's own paralyzed limbs. For such applications, we developed a real-time system that uses Bayesian inference techniques to estimate hand motion from the firing rates of multiple neurons. In this study, we used recordings that were previously made in the arm area of primary motor cortex in awake behaving monkeys using a chronically implanted multielectrode microarray. Bayesian inference involves computing the posterior probability of the hand motion conditioned on a sequence of observed firing rates; this is formulated in terms of the product of a likelihood and a prior. The likelihood term models the probability of firing rates given a particular hand motion. We found that a linear gaussian model could be used to approximate this likelihood and could be readily learned from a small amount of training data. The prior term defines a probabilistic model of hand kinematics and was also taken to be a linear gaussian model. Decoding was performed using a Kalman filter, which gives an efficient recursive method for Bayesian inference when the likelihood and prior are linear and gaussian. In off-line experiments, the Kalman filter reconstructions of hand trajectory were more accurate than previously reported results. The resulting decoding algorithm provides a principled probabilistic model of motor-cortical coding, decodes hand motion in real time, provides an estimate of uncertainty, and is straightforward to implement. Additionally the formulation unifies and extends previous models of neural coding while providing insights into the motor-cortical code.

pdf preprint pdf from publisher abstract [BibTex]

Wu, W., Gao, Y., Bienenstock, E., Donoghue, J. P., Black, M. J. Bayesian population decoding of motor cortical activity using a Kalman filter Neural Computation, 18(1):80-118, 2006 (article)

pdf preprint pdf from publisher abstract [BibTex]

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Hierarchical Approach for Articulated 3D Pose-Estimation and Tracking (extended abstract)

Sigal, L., Black, M. J.

In Learning, Representation and Context for Human Sensing in Video Workshop (in conjunction with CVPR), 2006 (inproceedings)

pdf poster [BibTex]

Sigal, L., Black, M. J. Hierarchical Approach for Articulated 3D Pose-Estimation and Tracking (extended abstract) In Learning, Representation and Context for Human Sensing in Video Workshop (in conjunction with CVPR), 2006 (inproceedings)

pdf poster [BibTex]

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Nonlinear physically-based models for decoding motor-cortical population activity

Shakhnarovich, G., Kim, S., Black, M. J.

In Advances in Neural Information Processing Systems 19, NIPS-2006, pages: 1257-1264, MIT Press, 2006 (inproceedings)

pdf [BibTex]

Shakhnarovich, G., Kim, S., Black, M. J. Nonlinear physically-based models for decoding motor-cortical population activity In Advances in Neural Information Processing Systems 19, NIPS-2006, pages: 1257-1264, MIT Press, 2006 (inproceedings)

pdf [BibTex]

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A comparison of decoding models for imagined motion from human motor cortex

Kim, S., Simeral, J., Donoghue, J. P., Hocherberg, L. R., Friehs, G., Mukand, J. A., Chen, D., Black, M. J.

Program No. 256.11. 2006 Abstract Viewer and Itinerary Planner, Society for Neuroscience, Atlanta, GA, 2006, Online (conference)

[BibTex]

Kim, S., Simeral, J., Donoghue, J. P., Hocherberg, L. R., Friehs, G., Mukand, J. A., Chen, D., Black, M. J. A comparison of decoding models for imagined motion from human motor cortex Program No. 256.11. 2006 Abstract Viewer and Itinerary Planner, Society for Neuroscience, Atlanta, GA, 2006, Online (conference)

[BibTex]

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Denoising archival films using a learned Bayesian model

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

In Int. Conf. on Image Processing, ICIP, pages: 2641-2644, Atlanta, 2006 (inproceedings)

pdf [BibTex]

Moldovan, T. M., Roth, S., Black, M. J. Denoising archival films using a learned Bayesian model In Int. Conf. on Image Processing, ICIP, pages: 2641-2644, Atlanta, 2006 (inproceedings)

pdf [BibTex]

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Efficient belief propagation with learned higher-order Markov random fields

Lan, X., Roth, S., Huttenlocher, D., Black, M. J.

In European Conference on Computer Vision, ECCV, II, pages: 269-282, Graz, Austria, 2006 (inproceedings)

pdf pdf from publisher [BibTex]

Lan, X., Roth, S., Huttenlocher, D., Black, M. J. Efficient belief propagation with learned higher-order Markov random fields In European Conference on Computer Vision, ECCV, II, pages: 269-282, Graz, Austria, 2006 (inproceedings)

pdf pdf from publisher [BibTex]

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Modeling neural control of physically realistic movement

Shaknarovich, G., Kim, S., Donoghue, J. P., Hocherberg, L. R., Friehs, G., Mukand, J. A., Chen, D., Black, M. J.

Program No. 256.12. 2006 Abstract Viewer and Itinerary Planner, Society for Neuroscience, Atlanta, GA, 2006, Online (conference)

[BibTex]

Shaknarovich, G., Kim, S., Donoghue, J. P., Hocherberg, L. R., Friehs, G., Mukand, J. A., Chen, D., Black, M. J. Modeling neural control of physically realistic movement Program No. 256.12. 2006 Abstract Viewer and Itinerary Planner, Society for Neuroscience, Atlanta, GA, 2006, Online (conference)

[BibTex]

2001

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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

De la Torre, F., Black, M. J. Dynamic coupled component analysis In IEEE Proc. Computer Vision and Pattern Recognition, CVPR’01, 2, pages: 643-650, IEEE, Kauai, Hawaii, December 2001 (inproceedings)

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]

De la Torre, F., Black, M. J. Robust principal component analysis for computer vision In Int. Conf. on Computer Vision, ICCV-2001, II, pages: 362-369, Vancouver, BC, USA, 2001 (inproceedings)

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]

Sidenbladh, H., Black, M. J. Learning image statistics for Bayesian tracking In Int. Conf. on Computer Vision, ICCV-2001, II, pages: 709-716, Vancouver, BC, USA, 2001 (inproceedings)

pdf [BibTex]

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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]

Gao, Y., Bienenstock, E., Black, M., Shoham, S., Serruya, M., Donoghue, J. Encoding/decoding of arm kinematics from simultaneously recorded MI neurons Society for Neuroscience Abst. Vol. 27, Program No. 572.14, 2001 (conference)

abstract [BibTex]

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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]

Ormoneit, D., Sidenbladh, H., Black, M. J., Hastie, T. Learning and tracking cyclic human motion 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]

1996

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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.

pdf [BibTex]

1996

Ju, S. X., Black, M. J., Yacoob, Y. Cardboard people: A parameterized model of articulated motion In 2nd Int. Conf. on Automatic Face- and Gesture-Recognition, pages: 38-44, Killington, Vermont, October 1996 (inproceedings)

pdf [BibTex]

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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.

pdf pdf from publisher [BibTex]

Black, M. J., Jepson, A. Estimating optical flow in segmented images using variable-order parametric models with local deformations IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(10):972-986, October 1996 (article)

pdf pdf from publisher [BibTex]

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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.

pdf pdf from publisher DOI [BibTex]

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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)

pdf [BibTex]

Ju, S., Black, M. J., Jepson, A. D. Skin and Bones: Multi-layer, locally affine, optical flow and regularization with transparency In IEEE Conf. on Computer Vision and Pattern Recognition, CVPR’96, pages: 307-314, San Francisco, CA, June 1996 (inproceedings)

pdf [BibTex]

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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)

pdf video [BibTex]

Black, M. J., Jepson, A. EigenTracking: Robust matching and tracking of articulated objects using a view-based representation In Proc. Fourth European Conf. on Computer Vision, ECCV’96, pages: 329-342, LNCS 1064, Springer Verlag, Cambridge, England, April 1996 (inproceedings)

pdf video [BibTex]

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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

pdf [BibTex]

Jepson, A., Black, M. Mixture Models for Image Representation PRECARN ARK Project Technical Report ARK96-PUB-54, March 1996 (techreport)

pdf [BibTex]

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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.

pdf pdf from publisher [BibTex]

Black, M. J., Anandan, P. The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields Computer Vision and Image Understanding, 63(1):75-104, January 1996 (article)

pdf pdf from publisher [BibTex]

1992

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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]

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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]

1990

Thumb xl bildschirmfoto 2013 01 14 um 12.09.14
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]