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2013


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Branch&Rank for Efficient Object Detection

Lehmann, A., Gehler, P., VanGool, L.

International Journal of Computer Vision, Springer, December 2013 (article)

Abstract
Ranking hypothesis sets is a powerful concept for efficient object detection. In this work, we propose a branch&rank scheme that detects objects with often less than 100 ranking operations. This efficiency enables the use of strong and also costly classifiers like non-linear SVMs with RBF-TeX kernels. We thereby relieve an inherent limitation of branch&bound methods as bounds are often not tight enough to be effective in practice. Our approach features three key components: a ranking function that operates on sets of hypotheses and a grouping of these into different tasks. Detection efficiency results from adaptively sub-dividing the object search space into decreasingly smaller sets. This is inherited from branch&bound, while the ranking function supersedes a tight bound which is often unavailable (except for rather limited function classes). The grouping makes the system effective: it separates image classification from object recognition, yet combines them in a single formulation, phrased as a structured SVM problem. A novel aspect of branch&rank is that a better ranking function is expected to decrease the number of classifier calls during detection. We use the VOC’07 dataset to demonstrate the algorithmic properties of branch&rank.

pdf link (url) [BibTex]

2013

pdf link (url) [BibTex]


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Extracting Postural Synergies for Robotic Grasping

Romero, J., Feix, T., Ek, C., Kjellstrom, H., Kragic, D.

Robotics, IEEE Transactions on, 29(6):1342-1352, December 2013 (article)

[BibTex]

[BibTex]


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Markov Random Field Modeling, Inference & Learning in Computer Vision & Image Understanding: A Survey

Wang, C., Komodakis, N., Paragios, N.

Computer Vision and Image Understanding (CVIU), 117(11):1610-1627, November 2013 (article)

Abstract
In this paper, we present a comprehensive survey of Markov Random Fields (MRFs) in computer vision and image understanding, with respect to the modeling, the inference and the learning. While MRFs were introduced into the computer vision field about two decades ago, they started to become a ubiquitous tool for solving visual perception problems around the turn of the millennium following the emergence of efficient inference methods. During the past decade, a variety of MRF models as well as inference and learning methods have been developed for addressing numerous low, mid and high-level vision problems. While most of the literature concerns pairwise MRFs, in recent years we have also witnessed significant progress in higher-order MRFs, which substantially enhances the expressiveness of graph-based models and expands the domain of solvable problems. This survey provides a compact and informative summary of the major literature in this research topic.

Publishers site pdf [BibTex]

Publishers site pdf [BibTex]


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Multi-robot cooperative spherical-object tracking in 3D space based on particle filters

Ahmad, A., Lima, P.

Robotics and Autonomous Systems, 61(10):1084-1093, October 2013 (article)

Abstract
This article presents a cooperative approach for tracking a moving spherical object in 3D space by a team of mobile robots equipped with sensors, in a highly dynamic environment. The tracker’s core is a particle filter, modified to handle, within a single unified framework, the problem of complete or partial occlusion for some of the involved mobile sensors, as well as inconsistent estimates in the global frame among sensors, due to observation errors and/or self-localization uncertainty. We present results supporting our approach by applying it to a team of real soccer robots tracking a soccer ball, including comparison with ground truth.

DOI [BibTex]

DOI [BibTex]


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Puppet Flow

Zuffi, S., Black, M. J.

(7), Max Planck Institute for Intelligent Systems, October 2013 (techreport)

Abstract
We introduce Puppet Flow (PF), a layered model describing the optical flow of a person in a video sequence. We consider video frames composed by two layers: a foreground layer corresponding to a person, and background. We model the background as an affine flow field. The foreground layer, being a moving person, requires reasoning about the articulated nature of the human body. We thus represent the foreground layer with the Deformable Structures model (DS), a parametrized 2D part-based human body representation. We call the motion field defined through articulated motion and deformation of the DS model, a Puppet Flow. By exploiting the DS representation, Puppet Flow is a parametrized optical flow field, where parameters are the person's pose, gender and body shape.

pdf Project Page Project Page [BibTex]

pdf Project Page Project Page [BibTex]


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D2.1.4 RoCKIn@Work - Innovation in Mobile Industrial Manipulation Competition Design, Rule Book, and Scenario Construction

Ahmad, A., Awaad, I., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schneider, S.

(FP7-ICT-601012 Revision 0.7), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, sep 2013 (techreport)

Abstract
RoCKIn is a EU-funded project aiming to foster scientific progress and innovation in cognitive systems and robotics through the design and implementation of competitions. An additional objective of RoCKIn is to increase public awareness of the current state-of-the-art in robotics in Europe and to demonstrate the innovation potential of robotics applications for solving societal challenges and improving the competitiveness of Europe in the global markets. In order to achieve these objectives, RoCKIn develops two competitions, one for domestic service robots (RoCKIn@Home) and one for industrial robots in factories (RoCKIn-@Work). These competitions are designed around challenges that are based on easy-to-communicate and convincing user stories, which catch the interest of both the general public and the scientifc community. The latter is in particular interested in solving open scientific challenges and to thoroughly assess, compare, and evaluate the developed approaches with competing ones. To allow this to happen, the competitions are designed to meet the requirements of benchmarking procedures and good experimental methods. The integration of benchmarking technology with the competition concept is one of the main objectives of RoCKIn. This document describes the first version of the RoCKIn@Work competition, which will be held for the first time in 2014. The first chapter of the document gives a brief overview, outlining the purpose and objective of the competition, the methodological approach taken by the RoCKIn project, the user story upon which the competition is based, the structure and organization of the competition, and the commonalities and differences with the RoboCup@Work competition, which served as inspiration for RoCKIn@Work. The second chapter provides details on the user story and analyzes the scientific and technical challenges it poses. Consecutive chapters detail the competition scenario, the competition design, and the organization of the competition. The appendices contain information on a library of functionalities, which we believe are needed, or at least useful, for building competition entries, details on the scenario construction, and a detailed account of the benchmarking infrastructure needed — and provided by RoCKIn.

[BibTex]

[BibTex]


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D2.1.1 RoCKIn@Home - A Competition for Domestic Service Robots Competition Design, Rule Book, and Scenario Construction

Ahmad, A., Awaad, I., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schneider, S.

(FP7-ICT-601012 Revision 0.7), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, sep 2013 (techreport)

Abstract
RoCKIn is a EU-funded project aiming to foster scientific progress and innovation in cognitive systems and robotics through the design and implementation of competitions. An additional objective of RoCKIn is to increase public awareness of the current state-of-the-art in robotics in Europe and to demonstrate the innovation potential of robotics applications for solving societal challenges and improving the competitiveness of Europe in the global markets. In order to achieve these objectives, RoCKIn develops two competitions, one for domestic service robots (RoCKIn@Home) and one for industrial robots in factories (RoCKIn-@Work). These competitions are designed around challenges that are based on easy-to-communicate and convincing user stories, which catch the interest of both the general public and the scientifc community. The latter is in particular interested in solving open scientific challenges and to thoroughly assess, compare, and evaluate the developed approaches with competing ones. To allow this to happen, the competitions are designed to meet the requirements of benchmarking procedures and good experimental methods. The integration of benchmarking technology with the competition concept is one of the main objectives of RoCKIn. This document describes the first version of the RoCKIn@Home competition, which will be held for the first time in 2014. The first chapter of the document gives a brief overview, outlining the purpose and objective of the competition, the methodological approach taken by the RoCKIn project, the user story upon which the competition is based, the structure and organization of the competition, and the commonalities and differences with the RoboCup@Home competition, which served as inspiration for RoCKIn@Home. The second chapter provides details on the user story and analyzes the scientific and technical challenges it poses. Consecutive chapters detail the competition scenario, the competition design, and the organization of the competition. The appendices contain information on a library of functionalities, which we believe are needed, or at least useful, for building competition entries, details on the scenario construction, and a detailed account of the benchmarking infrastructure needed — and provided by RoCKIn.

[BibTex]

[BibTex]


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Vision meets Robotics: The KITTI Dataset

Geiger, A., Lenz, P., Stiller, C., Urtasun, R.

International Journal of Robotics Research, 32(11):1231 - 1237 , Sage Publishing, September 2013 (article)

Abstract
We present a novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research. In total, we recorded 6 hours of traffic scenarios at 10-100 Hz using a variety of sensor modalities such as high-resolution color and grayscale stereo cameras, a Velodyne 3D laser scanner and a high-precision GPS/IMU inertial navigation system. The scenarios are diverse, capturing real-world traffic situations and range from freeways over rural areas to inner-city scenes with many static and dynamic objects. Our data is calibrated, synchronized and timestamped, and we provide the rectified and raw image sequences. Our dataset also contains object labels in the form of 3D tracklets and we provide online benchmarks for stereo, optical flow, object detection and other tasks. This paper describes our recording platform, the data format and the utilities that we provide.

pdf DOI [BibTex]

pdf DOI [BibTex]


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Human Pose Calculation from Optical Flow Data

Black, M., Loper, M., Romero, J., Zuffi, S.

European Patent Application EP 2843621 , August 2013 (patent)

Google Patents [BibTex]

Google Patents [BibTex]


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D1.1 Specification of General Features of Scenarios and Robots for Benchmarking Through Competitions

Ahmad, A., Awaad, I., Amigoni, F., Berghofer, J., Bischoff, R., Bonarini, A., Dwiputra, R., Fontana, G., Hegger, F., Hochgeschwender, N., Iocchi, L., Kraetzschmar, G., Lima, P., Matteucci, M., Nardi, D., Schiaffonati, V., Schneider, S.

(FP7-ICT-601012 Revision 1.0), RoCKIn - Robot Competitions Kick Innovation in Cognitive Systems and Robotics, July 2013 (techreport)

Abstract
RoCKIn is a EU-funded project aiming to foster scientific progress and innovation in cognitive systems and robotics through the design and implementation of competitions. An additional objective of RoCKIn is to increase public awareness of the current state-of-the-art in robotics and the innovation potential of robotics applications. From these objectives several requirements for the work performed in RoCKIn can be derived: The RoCKIn competitions must start from convincing, easy-to-communicate user stories, that catch the attention of relevant stakeholders, the media, and the crowd. The user stories play the role of a mid- to long-term vision for a competition. Preferably, the user stories address economic, societal, or environmental problems. The RoCKIn competitions must pose open scientific challenges of interest to sufficiently many researchers to attract existing and new teams of robotics researchers for participation in the competition. The competitions need to promise some suitable reward, such as recognition in the scientific community, publicity for a team’s work, awards, or prize money, to justify the effort a team puts into the development of a competition entry. The competitions should be designed in such a way that they reward general, scientifically sound solutions to the challenge problems; such general solutions should score better than approaches that work only in narrowly defined contexts and are considred over-engineered. The challenges motivating the RoCKIn competitions must be broken down into suitable intermediate goals that can be reached with a limited team effort until the next competition and the project duration. The RoCKIn competitions must be well-defined and well-designed, with comprehensive rule books and instructions for the participants in order to guarantee a fair competition. The RoCKIn competitions must integrate competitions with benchmarking in order to provide comprehensive feedback for the teams about the suitability of particular functional modules, their overall architecture, and system integration. This document takes the first steps towards the RoCKIn goals. After outlining our approach, we present several user stories for further discussion within the community. The main objectives of this document are to identify and document relevant scenario features and the tasks and functionalities subject for benchmarking in the competitions.

[BibTex]

[BibTex]


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SocRob-MSL 2013 Team Description Paper for Middle Sized League

Messias, J., Ahmad, A., Reis, J., Serafim, M., Lima, P.

17th Annual RoboCup International Symposium 2013, July 2013 (techreport)

Abstract
This paper describes the status of the SocRob MSL robotic soccer team as required by the RoboCup 2013 qualification procedures. The team’s latest scientific and technical developments, since its last participation in RoboCup MSL, include further advances in cooperative perception; novel communication methods for distributed robotics; progressive deployment of the ROS middleware; improved localization through feature tracking and Mixture MCL; novel planning methods based on Petri nets and decision-theoretic frameworks; and hardware developments in ball-handling/kicking devices.

link (url) [BibTex]

link (url) [BibTex]


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Visualizing dimensionality reduction of systems biology data

Lehrmann, A. M., Huber, M., Polatkan, A. C., Pritzkau, A., Nieselt, K.

Data Mining and Knowledge Discovery, 1(27):146-165, Springer, July 2013 (article)

pdf SpRay [BibTex]

pdf SpRay [BibTex]


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Unscented Kalman Filtering on Riemannian Manifolds

Soren Hauberg, Francois Lauze, Kim S. Pedersen

Journal of Mathematical Imaging and Vision, 46(1):103-120, Springer Netherlands, May 2013 (article)

Publishers site PDF [BibTex]

Publishers site PDF [BibTex]


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System and method for generating bilinear spatiotemporal basis models

Matthews, I. A. I. S. T. S. K. S. Y.

US Patent Application 13/425,369, March 2013 (patent)

Abstract
Techniques are disclosed for generating a bilinear spatiotemporal basis model. A method includes the steps of predefining a trajectory basis for the bilinear spatiotemporal basis model, receiving three-dimensional spatiotemporal data for a training sequence, estimating a shape basis for the bilinear spatiotemporal basis model using the three-dimensional spatiotemporal data, and computing coefficients for the bilinear spatiotemporal basis model using the trajectory basis and the shape basis.

Google Patents [BibTex]


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Quasi-Newton Methods: A New Direction

Hennig, P., Kiefel, M.

Journal of Machine Learning Research, 14(1):843-865, March 2013 (article)

Abstract
Four decades after their invention, quasi-Newton methods are still state of the art in unconstrained numerical optimization. Although not usually interpreted thus, these are learning algorithms that fit a local quadratic approximation to the objective function. We show that many, including the most popular, quasi-Newton methods can be interpreted as approximations of Bayesian linear regression under varying prior assumptions. This new notion elucidates some shortcomings of classical algorithms, and lights the way to a novel nonparametric quasi-Newton method, which is able to make more efficient use of available information at computational cost similar to its predecessors.

website+code pdf link (url) [BibTex]

website+code pdf link (url) [BibTex]


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A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them

Sun, D., Roth, S., Black, M. J.

(CS-10-03), Brown University, Department of Computer Science, January 2013 (techreport)

pdf [BibTex]

pdf [BibTex]


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Simultaneous Cast Shadows, Illumination and Geometry Inference Using Hypergraphs

Panagopoulos, A., Wang, C., Samaras, D., Paragios, N.

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 35(2):437-449, 2013 (article)

pdf [BibTex]

pdf [BibTex]


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Random Forests for Real Time 3D Face Analysis

Fanelli, G., Dantone, M., Gall, J., Fossati, A., van Gool, L.

International Journal of Computer Vision, 101(3):437-458, Springer, 2013 (article)

Abstract
We present a random forest-based framework for real time head pose estimation from depth images and extend it to localize a set of facial features in 3D. Our algorithm takes a voting approach, where each patch extracted from the depth image can directly cast a vote for the head pose or each of the facial features. Our system proves capable of handling large rotations, partial occlusions, and the noisy depth data acquired using commercial sensors. Moreover, the algorithm works on each frame independently and achieves real time performance without resorting to parallel computations on a GPU. We present extensive experiments on publicly available, challenging datasets and present a new annotated head pose database recorded using a Microsoft Kinect.

data and code publisher's site pdf DOI Project Page [BibTex]

data and code publisher's site pdf DOI Project Page [BibTex]


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Markerless Motion Capture of Multiple Characters Using Multi-view Image Segmentation

Liu, Y., Gall, J., Stoll, C., Dai, Q., Seidel, H., Theobalt, C.

Transactions on Pattern Analysis and Machine Intelligence, 35(11):2720-2735, 2013 (article)

Abstract
Capturing the skeleton motion and detailed time-varying surface geometry of multiple, closely interacting peoples is a very challenging task, even in a multicamera setup, due to frequent occlusions and ambiguities in feature-to-person assignments. To address this task, we propose a framework that exploits multiview image segmentation. To this end, a probabilistic shape and appearance model is employed to segment the input images and to assign each pixel uniquely to one person. Given the articulated template models of each person and the labeled pixels, a combined optimization scheme, which splits the skeleton pose optimization problem into a local one and a lower dimensional global one, is applied one by one to each individual, followed with surface estimation to capture detailed nonrigid deformations. We show on various sequences that our approach can capture the 3D motion of humans accurately even if they move rapidly, if they wear wide apparel, and if they are engaged in challenging multiperson motions, including dancing, wrestling, and hugging.

data and video pdf DOI Project Page [BibTex]

data and video pdf DOI Project Page [BibTex]


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Viewpoint and pose in body-form adaptation

Sekunova, A., Black, M., Parkinson, L., Barton, J. J. S.

Perception, 42(2):176-186, 2013 (article)

Abstract
Faces and bodies are complex structures, perception of which can play important roles in person identification and inference of emotional state. Face representations have been explored using behavioural adaptation: in particular, studies have shown that face aftereffects show relatively broad tuning for viewpoint, consistent with origin in a high-level structural descriptor far removed from the retinal image. Our goals were to determine first, if body aftereffects also showed a degree of viewpoint invariance, and second if they also showed pose invariance, given that changes in pose create even more dramatic changes in the 2-D retinal image. We used a 3-D model of the human body to generate headless body images, whose parameters could be varied to generate different body forms, viewpoints, and poses. In the first experiment, subjects adapted to varying viewpoints of either slim or heavy bodies in a neutral stance, followed by test stimuli that were all front-facing. In the second experiment, we used the same front-facing bodies in neutral stance as test stimuli, but compared adaptation from bodies in the same neutral stance to adaptation with the same bodies in different poses. We found that body aftereffects were obtained over substantial viewpoint changes, with no significant decline in aftereffect magnitude with increasing viewpoint difference between adapting and test images. Aftereffects also showed transfer across one change in pose but not across another. We conclude that body representations may have more viewpoint invariance than faces, and demonstrate at least some transfer across pose, consistent with a high-level structural description. Keywords: aftereffect, shape, face, representation

pdf from publisher abstract pdf link (url) Project Page [BibTex]

pdf from publisher abstract pdf link (url) Project Page [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]

2006


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Implicit Wiener Series, Part II: Regularised estimation

Gehler, P., Franz, M.

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

pdf [BibTex]

2006


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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]

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]

pdf preprint pdf from publisher abstract [BibTex]

2004


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On the variability of manual spike sorting

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

IEEE Trans. Biomedical Engineering, 51(6):912-918, June 2004 (article)

pdf pdf from publisher [BibTex]

2004

pdf pdf from publisher [BibTex]


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Modeling and decoding motor cortical activity using a switching Kalman filter

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

IEEE Trans. Biomedical Engineering, 51(6):933-942, June 2004 (article)

Abstract
We present a switching Kalman filter model for the real-time inference of hand kinematics from a population of motor cortical neurons. Firing rates are modeled as a Gaussian mixture where the mean of each Gaussian component is a linear function of hand kinematics. A “hidden state” models the probability of each mixture component and evolves over time in a Markov chain. The model generalizes previous encoding and decoding methods, addresses the non-Gaussian nature of firing rates, and can cope with crudely sorted neural data common in on-line prosthetic applications.

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]

1996


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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]

1996

pdf pdf from publisher [BibTex]


Thumb xl bildschirmfoto 2012 12 07 um 11.59.00
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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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]

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]

pdf pdf from publisher [BibTex]


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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]