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2013


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Reconstructing patient-specific cardiac models from contours via Delaunay triangulation and graph-cuts

Min Wan, Calvin Lim, Junmei Zhang, Yi Su, Si Yong Yeo, Desheng Wang, Ru San Tan, Liang Zhong

In International Conference of the IEEE Engineering in Medicine and Biology Society, pages: 2976-9, 2013 (inproceedings)

[BibTex]

2013

[BibTex]


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Regional comparison of left ventricle systolic wall stress reveals intraregional uniformity in healthy subjects

Soo Kng Teo, Si Yong Yeo, May Ling Tan, Chi Wan Lim, Liang Zhong, Ru San Tan, Yi Su

In Computing in Cardiology Conference, pages: 575 - 578, 2013 (inproceedings)

Abstract
This study aimed to assess the feasibility of using the regional uniformity of the left ventricle (LV) wall stress (WS) to diagnose patients with myocardial infarction. We present a novel method using a similarity map that measures the degree of uniformity in nominal systolic WS across pairs of segments within the same patient. The values of the nominal WS are computed at each vertex point from a 1-to-1 corresponding mesh pair of the LV at the end-diastole (ED) and end-systole (ES) phases. The 3D geometries of the LV at ED and ES are reconstructed from border-delineated MRI images and the 1-to-1 mesh generated using a strain-energy minimization approach. The LV is then partitioned into 16 segments based on published clinical standard and the nominal WS histogram distribution for each of the segment was computed. A similarity index is then computed for each pair of histogram distributions to generate a 16-by-16 similarity map. Based on our initial study involving 12 MI patients and 9 controls, we observed uniformity for intra- regional comparisons in the controls compared against the patients. Our results suggest that the regional uniformity of the nominal systolic WS in the form of a similarity map can potentially be used as a discriminant between MI patients and normal controls.

[BibTex]

[BibTex]


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Class-Specific Hough Forests for Object Detection

Gall, J., Lempitsky, V.

In Decision Forests for Computer Vision and Medical Image Analysis, pages: 143-157, 11, (Editors: Criminisi, A. and Shotton, J.), Springer, 2013 (incollection)

code Project Page [BibTex]

code Project Page [BibTex]


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Image Gradient Based Level Set Methods in 2D and 3D

Xianhua Xie, Si Yong Yeo, Majid Mirmehdi, Igor Sazonov, Perumal Nithiarasu

In Deformation Models: Tracking, Animation and Applications, pages: 101-120, 0, (Editors: Manuel González Hidalgo and Arnau Mir Torres and Javier Varona Gómez), Springer, 2013 (inbook)

Abstract
This chapter presents an image gradient based approach to perform 2D and 3D deformable model segmentation using level set. The 2D method uses an external force field that is based on magnetostatics and hypothesized magnetic interactions between the active contour and object boundaries. The major contribution of the method is that the interaction of its forces can greatly improve the active contour in capturing complex geometries and dealing with difficult initializations, weak edges and broken boundaries. This method is then generalized to 3D by reformulating its external force based on geometrical interactions between the relative geometries of the deformable model and the object boundary characterized by image gradient. The evolution of the deformable model is solved using the level set method so that topological changes are handled automatically. The relative geometrical configurations between the deformable model and the object boundaries contribute to a dynamic vector force field that changes accordingly as the deformable model evolves. The geometrically induced dynamic interaction force has been shown to greatly improve the deformable model performance in acquiring complex geometries and highly concave boundaries, and it gives the deformable model a high invariancy in initialization configurations. The voxel interactions across the whole image domain provide a global view of the object boundary representation, giving the external force a long attraction range. The bidirectionality of the external force field allows the new deformable model to deal with arbitrary cross-boundary initializations, and facilitates the handling of weak edges and broken boundaries.

[BibTex]

[BibTex]


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Non-parametric hand pose estimation with object context

Romero, J., Kjellström, H., Ek, C. H., Kragic, D.

Image and Vision Computing , 31(8):555 - 564, 2013 (article)

Abstract
In the spirit of recent work on contextual recognition and estimation, we present a method for estimating the pose of human hands, employing information about the shape of the object in the hand. Despite the fact that most applications of human hand tracking involve grasping and manipulation of objects, the majority of methods in the literature assume a free hand, isolated from the surrounding environment. Occlusion of the hand from grasped objects does in fact often pose a severe challenge to the estimation of hand pose. In the presented method, object occlusion is not only compensated for, it contributes to the pose estimation in a contextual fashion; this without an explicit model of object shape. Our hand tracking method is non-parametric, performing a nearest neighbor search in a large database (.. entries) of hand poses with and without grasped objects. The system that operates in real time, is robust to self occlusions, object occlusions and segmentation errors, and provides full hand pose reconstruction from monocular video. Temporal consistency in hand pose is taken into account, without explicitly tracking the hand in the high-dim pose space. Experiments show the non-parametric method to outperform other state of the art regression methods, while operating at a significantly lower computational cost than comparable model-based hand tracking methods.

Publisher site pdf link (url) [BibTex]

Publisher site pdf link (url) [BibTex]

2003


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Image statistics and anisotropic diffusion

Scharr, H., Black, M. J., Haussecker, H.

In Int. Conf. on Computer Vision, pages: 840-847, October 2003 (inproceedings)

pdf [BibTex]

2003

pdf [BibTex]


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A switching Kalman filter model for the motor cortical coding of hand motion

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

In Proc. IEEE Engineering in Medicine and Biology Society, pages: 2083-2086, September 2003 (inproceedings)

pdf [BibTex]

pdf [BibTex]


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Learning the statistics of people in images and video

Sidenbladh, H., Black, M. J.

International Journal of Computer Vision, 54(1-3):183-209, August 2003 (article)

Abstract
This paper address the problems of modeling the appearance of humans and distinguishing human appearance from the appearance of general scenes. We seek a model of appearance and motion that is generic in that it accounts for the ways in which people's appearance varies and, at the same time, is specific enough to be useful for tracking people in natural scenes. Given a 3D model of the person projected into an image we model the likelihood of observing various image cues conditioned on the predicted locations and orientations of the limbs. These cues are taken to be steered filter responses corresponding to edges, ridges, and motion-compensated temporal differences. Motivated by work on the statistics of natural scenes, the statistics of these filter responses for human limbs are learned from training images containing hand-labeled limb regions. Similarly, the statistics of the filter responses in general scenes are learned to define a “background” distribution. The likelihood of observing a scene given a predicted pose of a person is computed, for each limb, using the likelihood ratio between the learned foreground (person) and background distributions. Adopting a Bayesian formulation allows cues to be combined in a principled way. Furthermore, the use of learned distributions obviates the need for hand-tuned image noise models and thresholds. The paper provides a detailed analysis of the statistics of how people appear in scenes and provides a connection between work on natural image statistics and the Bayesian tracking of people.

pdf pdf from publisher code DOI [BibTex]

pdf pdf from publisher code DOI [BibTex]


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A framework for robust subspace learning

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

International Journal of Computer Vision, 54(1-3):117-142, August 2003 (article)

Abstract
Many computer vision, signal processing and statistical problems can be posed as problems of learning low dimensional linear or multi-linear models. These models have been widely used for the representation of shape, appearance, motion, etc., in computer vision applications. Methods for learning linear models can be seen as a special case of subspace fitting. One draw-back of previous learning methods is that they are based on least squares estimation techniques and hence fail to account for “outliers” which are common in realistic training sets. We review previous approaches for making linear learning methods robust to outliers and present a new method that uses an intra-sample outlier process to account for pixel outliers. We develop the theory of Robust Subspace Learning (RSL) for linear models within a continuous optimization framework based on robust M-estimation. The framework applies to a variety of linear learning problems in computer vision including eigen-analysis and structure from motion. Several synthetic and natural examples are used to develop and illustrate the theory and applications of robust subspace learning in computer vision.

pdf code pdf from publisher Project Page [BibTex]

pdf code pdf from publisher Project Page [BibTex]


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Guest editorial: Computational vision at Brown

Black, M. J., Kimia, B.

International Journal of Computer Vision, 54(1-3):5-11, August 2003 (article)

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


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Robust parameterized component analysis: Theory and applications to 2D facial appearance models

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

Computer Vision and Image Understanding, 91(1-2):53-71, July 2003 (article)

Abstract
Principal component analysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion in images. In particular, PCA has been widely used to model the variation in the appearance of people's faces. We extend previous work on facial modeling for tracking faces in video sequences as they undergo significant changes due to facial expressions. Here we consider person-specific facial appearance models (PSFAM), which use modular PCA to model complex intra-person appearance changes. Such models require aligned visual training data; in previous work, this has involved a time consuming and error-prone hand alignment and cropping process. Instead, the main contribution of this paper is to introduce parameterized component analysis to learn a subspace that is invariant to affine (or higher order) geometric transformations. The automatic learning of a PSFAM given a training image sequence is posed as a continuous optimization problem and is solved with a mixture of stochastic and deterministic techniques achieving sub-pixel accuracy. We illustrate the use of the 2D PSFAM model with preliminary experiments relevant to applications including video-conferencing and avatar animation.

pdf [BibTex]

pdf [BibTex]


no image
A Gaussian mixture model for the motor cortical coding of hand motion

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

Neural Control of Movement, Santa Barbara, CA, April 2003 (conference)

abstract [BibTex]

abstract [BibTex]


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Connecting brains with machines: The neural control of 2D cursor movement

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

In 1st International IEEE/EMBS Conference on Neural Engineering, pages: 580-583, Capri, Italy, March 2003 (inproceedings)

pdf [BibTex]

pdf [BibTex]


Thumb xl bildschirmfoto 2013 01 15 um 09.44.01
A quantitative comparison of linear and non-linear models of motor cortical activity for the encoding and decoding of arm motions

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

In 1st International IEEE/EMBS Conference on Neural Engineering, pages: 189-192, Capri, Italy, March 2003 (inproceedings)

pdf [BibTex]

pdf [BibTex]


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Accuracy of manual spike sorting: Results for the Utah intracortical array

Wood, F., Fellows, M., Vargas-Irwin, C., Black, M. J., Donoghue, J. P.

Program No. 279.2. 2003, Abstract Viewer and Itinerary Planner, Society for Neuroscience, Washington, DC, 2003, Online (conference)

abstract [BibTex]

abstract [BibTex]


no image
Specular flow and the perception of surface reflectance

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

Journal of Vision, 3 (9): 413a, 2003 (conference)

abstract poster [BibTex]

abstract poster [BibTex]


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Attractive people: Assembling loose-limbed models using non-parametric belief propagation

Sigal, L., Isard, M. I., Sigelman, B. H., Black, M. J.

In Advances in Neural Information Processing Systems 16, NIPS, pages: 1539-1546, (Editors: S. Thrun and L. K. Saul and B. Schölkopf), MIT Press, 2003 (inproceedings)

Abstract
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensionality of articulated body models. To cope with these problems we represent the 3D human body as a graphical model in which the relationships between the body parts are represented by conditional probability distributions. We formulate the pose estimation problem as one of probabilistic inference over a graphical model where the random variables correspond to the individual limb parameters (position and orientation). Because the limbs are described by 6-dimensional vectors encoding pose in 3-space, discretization is impractical and the random variables in our model must be continuous-valued. To approximate belief propagation in such a graph we exploit a recently introduced generalization of the particle filter. This framework facilitates the automatic initialization of the body-model from low level cues and is robust to occlusion of body parts and scene clutter.

pdf (color) pdf (black and white) [BibTex]

pdf (color) pdf (black and white) [BibTex]


Thumb xl bildschirmfoto 2013 01 15 um 09.48.31
Neural decoding of cursor motion using a Kalman filter

(Nominated: Best student paper)

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

In Advances in Neural Information Processing Systems 15, pages: 133-140, MIT Press, 2003 (inproceedings)

pdf [BibTex]

pdf [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]


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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]


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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]