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32 results (View BibTeX file of all listed publications)

2011

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High-quality reflection separation using polarized images

Kong, N., Tai, Y., Shin, S. Y.

IEEE Transactions on Image Processing, 20(12):3393-3405, IEEE Signal Processing Society, December 2011 (article)

Abstract
In this paper, we deal with a problem of separating the effect of reflection from images captured behind glass. The input consists of multiple polarized images captured from the same view point but with different polarizer angles. The output is the high quality separation of the reflection layer and the background layer from the images. We formulate this problem as a constrained optimization problem and propose a framework that allows us to fully exploit the mutually exclusive image information in our input data. We test our approach on various images and demonstrate that our approach can generate good reflection separation results.

Publisher site [BibTex]

2011

Kong, N., Tai, Y., Shin, S. Y. High-quality reflection separation using polarized images IEEE Transactions on Image Processing, 20(12):3393-3405, IEEE Signal Processing Society, December 2011 (article)

Publisher site [BibTex]

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A human inspired gaze estimation system

Wulff, J., Sinha, P.

Journal of Vision, 11(11):507-507, ARVO, September 2011 (article)

Abstract
Estimating another person's gaze is a crucial skill in human social interactions. The social component is most apparent in dyadic gaze situations, in which the looker seems to look into the eyes of the observer, thereby signaling interest or a turn to speak. In a triadic situation, on the other hand, the looker's gaze is averted from the observer and directed towards another, specific target. This is mostly interpreted as a cue for joint attention, creating awareness of a predator or another point of interest. In keeping with the task's social significance, humans are very proficient at gaze estimation. Our accuracy ranges from less than one degree for dyadic settings to approximately 2.5 degrees for triadic ones. Our goal in this work is to draw inspiration from human gaze estimation mechanisms in order to create an artificial system that can approach the former's accuracy levels. Since human performance is severely impaired by both image-based degradations (Ando, 2004) and a change of facial configurations (Jenkins & Langton, 2003), the underlying principles are believed to be based both on simple image cues such as contrast/brightness distribution and on more complex geometric processing to reconstruct the actual shape of the head. By incorporating both kinds of cues in our system's design, we are able to surpass the accuracy of existing eye-tracking systems, which rely exclusively on either image-based or geometry-based cues (Yamazoe et al., 2008). A side-benefit of this combined approach is that it allows for gaze estimation despite moderate view-point changes. This is important for settings where subjects, say young children or certain kinds of patients, might not be fully cooperative to allow a careful calibration. Our model and implementation of gaze estimation opens up new experimental questions about human mechanisms while also providing a useful tool for general calibration-free, non-intrusive remote eye-tracking.

link (url) DOI [BibTex]

Wulff, J., Sinha, P. A human inspired gaze estimation system Journal of Vision, 11(11):507-507, ARVO, September 2011 (article)

link (url) DOI [BibTex]

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Detecting synchrony in degraded audio-visual streams

Dhandhania, K., Wulff, J., Sinha, P.

Journal of Vision, 11(11):800-800, ARVO, September 2011 (article)

Abstract
Even 8–10 week old infants, when presented with two dynamic faces and a speech stream, look significantly longer at the ‘correct’ talking person (Patterson & Werker, 2003). This is true even though their reduced visual acuity prevents them from utilizing high spatial frequencies. Computational analyses in the field of audio/video synchrony and automatic speaker detection (e.g. Hershey & Movellan, 2000), in contrast, usually depend on high-resolution images. Therefore, the correlation mechanisms found in these computational studies are not directly applicable to the processes through which we learn to integrate the modalities of speech and vision. In this work, we investigated the correlation between speech signals and degraded video signals. We found a high correlation persisting even with high image degradation, resembling the low visual acuity of young infants. Additionally (in a fashion similar to Graf et al., 2002) we explored which parts of the face correlate with the audio in the degraded video sequences. Perfect synchrony and small offsets in the audio were used while finding the correlation, thereby detecting visual events preceding and following audio events. In order to achieve a sufficiently high temporal resolution, high-speed video sequences (500 frames per second) of talking people were used. This is a temporal resolution unachieved in previous studies and has allowed us to capture very subtle and short visual events. We believe that the results of this study might be interesting not only to vision researchers, but, by revealing subtle effects on a very fine timescale, also to people working in computer graphics and the generation and animation of artificial faces.

link (url) DOI [BibTex]

Dhandhania, K., Wulff, J., Sinha, P. Detecting synchrony in degraded audio-visual streams Journal of Vision, 11(11):800-800, ARVO, September 2011 (article)

link (url) DOI [BibTex]

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ISocRob-MSL 2011 Team Description Paper for Middle Sized League

Messias, J., Ahmad, A., Reis, J., Sousa, J., Lima, P.

15th Annual RoboCup International Symposium 2011, July 2011 (techreport)

Abstract
This paper describes the status of the ISocRob MSL robotic soccer team as required by the RoboCup 2011 qualification procedures. The most relevant technical and scientifical developments carried out by the team, since its last participation in the RoboCup MSL competitions, are here detailed. These include cooperative localization, cooperative object tracking, planning under uncertainty, obstacle detection and improvements to self-localization.

link (url) [BibTex]

Messias, J., Ahmad, A., Reis, J., Sousa, J., Lima, P. ISocRob-MSL 2011 Team Description Paper for Middle Sized League 15th Annual RoboCup International Symposium 2011, July 2011 (techreport)

link (url) [BibTex]

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Trajectory Space: A Dual Representation for Nonrigid Structure from Motion

Akhter, I., Sheikh, Y., Khan, S., Kanade, T.

Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(7):1442-1456, IEEE, July 2011 (article)

Abstract
Existing approaches to nonrigid structure from motion assume that the instantaneous 3D shape of a deforming object is a linear combination of basis shapes. These basis are object dependent and therefore have to be estimated anew for each video sequence. In contrast, we propose a dual approach to describe the evolving 3D structure in trajectory space by a linear combination of basis trajectories. We describe the dual relationship between the two approaches, showing that they both have equal power for representing 3D structure. We further show that the temporal smoothness in 3D trajectories alone can be used for recovering nonrigid structure from a moving camera. The principal advantage of expressing deforming 3D structure in trajectory space is that we can define an object independent basis. This results in a significant reduction in unknowns, and corresponding stability in estimation. We propose the use of the Discrete Cosine Transform (DCT) as the object independent basis and empirically demonstrate that it approaches Principal Component Analysis (PCA) for natural motions. We report the performance of the proposed method, quantitatively using motion capture data, and qualitatively on several video sequences exhibiting nonrigid motions including piecewise rigid motion, partially nonrigid motion (such as a facial expressions), and highly nonrigid motion (such as a person walking or dancing).

pdf project page [BibTex]

Akhter, I., Sheikh, Y., Khan, S., Kanade, T. Trajectory Space: A Dual Representation for Nonrigid Structure from Motion Pattern Analysis and Machine Intelligence, IEEE Transactions on, 33(7):1442-1456, IEEE, July 2011 (article)

pdf project page [BibTex]

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Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation

Sigal, L., Isard, M., Haussecker, H., Black, M. J.

International Journal of Computer Vision, 98(1):15-48, Springer Netherlands, May 2011 (article)

Abstract
We formulate the problem of 3D human pose estimation and tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loosely-connected body-parts. In particular, we model the body using an undirected graphical model in which nodes correspond to parts and edges to kinematic, penetration, and temporal constraints imposed by the joints and the world. These constraints are encoded using pair-wise statistical distributions, that are learned from motion-capture training data. Human pose and motion estimation is formulated as inference in this graphical model and is solved using Particle Message Passing (PaMPas). PaMPas is a form of non-parametric belief propagation that uses a variation of particle filtering that can be applied over a general graphical model with loops. The loose-limbed model and decentralized graph structure allow us to incorporate information from "bottom-up" visual cues, such as limb and head detectors, into the inference process. These detectors enable automatic initialization and aid recovery from transient tracking failures. We illustrate the method by automatically tracking people in multi-view imagery using a set of calibrated cameras and present quantitative evaluation using the HumanEva dataset.

pdf publisher's site link (url) Project Page Project Page [BibTex]

Sigal, L., Isard, M., Haussecker, H., Black, M. J. Loose-limbed People: Estimating 3D Human Pose and Motion Using Non-parametric Belief Propagation International Journal of Computer Vision, 98(1):15-48, Springer Netherlands, May 2011 (article)

pdf publisher's site link (url) Project Page Project Page [BibTex]

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Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia

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

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 19(2):193-203, April 2011 (article)

Abstract
We present a point-and-click intracortical neural interface system (NIS) that enables humans with tetraplegia to volitionally move a 2D computer cursor in any desired direction on a computer screen, hold it still and click on the area of interest. This direct brain-computer interface extracts both discrete (click) and continuous (cursor velocity) signals from a single small population of neurons in human motor cortex. A key component of this system is a multi-state probabilistic decoding algorithm that simultaneously decodes neural spiking activity and outputs either a click signal or the velocity of the cursor. The algorithm combines a linear classifier, which determines whether the user is intending to click or move the cursor, with a Kalman filter that translates the neural population activity into cursor velocity. We present a paradigm for training the multi-state decoding algorithm using neural activity observed during imagined actions. Two human participants with tetraplegia (paralysis of the four limbs) performed a closed-loop radial target acquisition task using the point-and-click NIS over multiple sessions. We quantified point-and-click performance using various human-computer interaction measurements for pointing devices. We found that participants were able to control the cursor motion accurately and click on specified targets with a small error rate (< 3% in one participant). This study suggests that signals from a small ensemble of motor cortical neurons (~40) can be used for natural point-and-click 2D cursor control of a personal computer.

pdf publishers's site pub med link (url) Project Page [BibTex]

Kim, S., Simeral, J. D., Hochberg, L. R., Donoghue, J. P., Friehs, G. M., Black, M. J. Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia IEEE Transactions on Neural Systems and Rehabilitation Engineering, 19(2):193-203, April 2011 (article)

pdf publishers's site pub med link (url) Project Page [BibTex]

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A Database and Evaluation Methodology for Optical Flow

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

International Journal of Computer Vision, 92(1):1-31, March 2011 (article)

Abstract
The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex natural scenes, including nonrigid motion, real sensor noise, and motion discontinuities. We propose a new set of benchmarks and evaluation methods for the next generation of optical flow algorithms. To that end, we contribute four types of data to test different aspects of optical flow algorithms: (1) sequences with nonrigid motion where the ground-truth flow is determined by tracking hidden fluorescent texture, (2) realistic synthetic sequences, (3) high frame-rate video used to study interpolation error, and (4) modified stereo sequences of static scenes. In addition to the average angular error used by Barron et al., we compute the absolute flow endpoint error, measures for frame interpolation error, improved statistics, and results at motion discontinuities and in textureless regions. In October 2007, we published the performance of several well-known methods on a preliminary version of our data to establish the current state of the art. We also made the data freely available on the web at http://vision.middlebury.edu/flow/ . Subsequently a number of researchers have uploaded their results to our website and published papers using the data. A significant improvement in performance has already been achieved. In this paper we analyze the results obtained to date and draw a large number of conclusions from them.

pdf pdf from publisher Middlebury Flow Evaluation Website [BibTex]

Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., Szeliski, R. A Database and Evaluation Methodology for Optical Flow International Journal of Computer Vision, 92(1):1-31, March 2011 (article)

pdf pdf from publisher Middlebury Flow Evaluation Website [BibTex]

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Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

(J. Neural Engineering Highlights of 2011 Collection. JNE top 10 cited papers of 2010-2011.)

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

J. of Neural Engineering, 8(2):025027, 2011 (article)

Abstract
The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor.

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

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Benchmark datasets for pose estimation and tracking

Andriluka, M., Sigal, L., Black, M. J.

In Visual Analysis of Humans: Looking at People, pages: 253-274, (Editors: Moesland and Hilton and Kr"uger and Sigal), Springer-Verlag, London, 2011 (incollection)

publisher's site Project Page [BibTex]

Andriluka, M., Sigal, L., Black, M. J. Benchmark datasets for pose estimation and tracking In Visual Analysis of Humans: Looking at People, pages: 253-274, (Editors: Moesland and Hilton and Kr"uger and Sigal), Springer-Verlag, London, 2011 (incollection)

publisher's site Project Page [BibTex]

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Fields of experts

Roth, S., Black, M. J.

In Markov Random Fields for Vision and Image Processing, pages: 297-310, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

Abstract
Fields of Experts are high-order Markov random field (MRF) models with potential functions that extend over large pixel neighborhoods. The clique potentials are modeled as a Product of Experts using nonlinear functions of many linear filter responses. In contrast to previous MRF approaches, all parameters, including the linear filters themselves, are learned from training data. A Field of Experts (FoE) provides a generic, expressive image prior that can capture the statistics of natural scenes, and can be used for a variety of machine vision tasks. The capabilities of FoEs are demonstrated with two example applications, image denoising and image inpainting, which are implemented using a simple, approximate inference scheme. While the FoE model is trained on a generic image database and is not tuned toward a specific application, the results compete with specialized techniques.

publisher site [BibTex]

Roth, S., Black, M. J. Fields of experts In Markov Random Fields for Vision and Image Processing, pages: 297-310, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

publisher site [BibTex]

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Dorsal Stream: From Algorithm to Neuroscience

Jhuang, H.

PhD Thesis, MIT, 2011 (techreport)

pdf [BibTex]

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Modelling pipeline for subject-specific arterial blood flow—A review

Igor Sazonov, Si Yong Yeo, Rhodri Bevan, Xianghua Xie, Raoul van Loon, Perumal Nithiarasu

International Journal for Numerical Methods in Biomedical Engineering, 27(12):1868–1910, 2011 (article)

Abstract
In this paper, a robust and semi-automatic modelling pipeline for blood flow through subject-specific arterial geometries is presented. The framework developed consists of image segmentation, domain discretization (meshing) and fluid dynamics. All the three subtopics of the pipeline are explained using an example of flow through a severely stenosed human carotid artery. In the Introduction, the state-of-the-art of both image segmentation and meshing is presented in some detail, and wherever possible the advantages and disadvantages of the existing methods are analysed. Followed by this, the deformable model used for image segmentation is presented. This model is based upon a geometrical potential force (GPF), which is a function of the image. Both the GPF calculation and level set determination are explained. Following the image segmentation method, a semi-automatic meshing method used in the present study is explained in full detail. All the relevant techniques required to generate a valid domain discretization are presented. These techniques include generating a valid surface mesh, skeletonization, mesh cropping, boundary layer mesh construction and various mesh cosmetic methods that are essential for generating a high-quality domain discretization. After presenting the mesh generation procedure, how to generate flow boundary conditions for both the inlets and outlets of a geometry is explained in detail. This is followed by a brief note on the flow solver, before studying the blood flow through the carotid artery with a severe stenosis.

[BibTex]

Igor Sazonov, Si Yong Yeo, Rhodri Bevan, Xianghua Xie, Raoul van Loon, Perumal Nithiarasu Modelling pipeline for subject-specific arterial blood flow—A review International Journal for Numerical Methods in Biomedical Engineering, 27(12):1868–1910, 2011 (article)

[BibTex]

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Geometrically Induced Force Interaction for Three-Dimensional Deformable Models

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

IEEE Transactions on Image Processing, 20(5):1373 - 1387, 2011 (article)

Abstract
In this paper, we propose a novel 3-D deformable model that is based upon a geometrically induced external force field which can be conveniently generalized to arbitrary dimensions. This external force field is based upon hypothesized 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. In addition, we show that by enhancing the geometrical interaction field with a nonlocal edge-preserving algorithm, the new deformable model can effectively overcome image noise. We provide a comparative study on the segmentation of various geometries with different topologies from both synthetic and real images, and show that the proposed method achieves significant improvements against existing image gradient techniques.

[BibTex]

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu Geometrically Induced Force Interaction for Three-Dimensional Deformable Models IEEE Transactions on Image Processing, 20(5):1373 - 1387, 2011 (article)

[BibTex]

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Steerable random fields for image restoration and inpainting

Roth, S., Black, M. J.

In Markov Random Fields for Vision and Image Processing, pages: 377-387, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

Abstract
This chapter introduces the concept of a Steerable Random Field (SRF). In contrast to traditional Markov random field (MRF) models in low-level vision, the random field potentials of a SRF are defined in terms of filter responses that are steered to the local image structure. This steering uses the structure tensor to obtain derivative responses that are either aligned with, or orthogonal to, the predominant local image structure. Analysis of the statistics of these steered filter responses in natural images leads to the model proposed here. Clique potentials are defined over steered filter responses using a Gaussian scale mixture model and are learned from training data. The SRF model connects random fields with anisotropic regularization and provides a statistical motivation for the latter. Steering the random field to the local image structure improves image denoising and inpainting performance compared with traditional pairwise MRFs.

publisher site [BibTex]

Roth, S., Black, M. J. Steerable random fields for image restoration and inpainting In Markov Random Fields for Vision and Image Processing, pages: 377-387, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

publisher site [BibTex]

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Model-Based Pose Estimation

Pons-Moll, G., Rosenhahn, B.

In Visual Analysis of Humans: Looking at People, pages: 139-170, 9, (Editors: T. Moeslund, A. Hilton, V. Krueger, L. Sigal), Springer, 2011 (inbook)

book page pdf [BibTex]

Pons-Moll, G., Rosenhahn, B. Model-Based Pose Estimation In Visual Analysis of Humans: Looking at People, pages: 139-170, 9, (Editors: T. Moeslund, A. Hilton, V. Krueger, L. Sigal), Springer, 2011 (inbook)

book page pdf [BibTex]

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Computational flow studies in a subject-specific human upper airway using a one-equation turbulence model. Influence of the nasal cavity

Prihambodo Saksono, Perumal Nithiarasu, Igor Sazonov, Si Yong Yeo

International Journal for Numerical Methods in Biomedical Engineering, 87(1-5):96–114, 2011 (article)

Abstract
This paper focuses on the impact of including nasal cavity on airflow through a human upper respiratory tract. A computational study is carried out on a realistic geometry, reconstructed from CT scans of a subject. The geometry includes nasal cavity, pharynx, larynx, trachea and two generations of airway bifurcations below trachea. The unstructured mesh generation procedure is discussed in some length due to the complex nature of the nasal cavity structure and poor scan resolution normally available from hospitals. The fluid dynamic studies have been carried out on the geometry with and without the inclusion of the nasal cavity. The characteristic-based split scheme along with the one-equation Spalart–Allmaras turbulence model is used in its explicit form to obtain flow solutions at steady state. Results reveal that the exclusion of nasal cavity significantly influences the resulting solution. In particular, the location of recirculating flow in the trachea is dramatically different when the truncated geometry is used. In addition, we also address the differences in the solution due to imposed, equally distributed and proportionally distributed flow rates at inlets (both nares). The results show that the differences in flow pattern between the two inlet conditions are not confined to the nasal cavity and nasopharyngeal region, but they propagate down to the trachea.

[BibTex]

Prihambodo Saksono, Perumal Nithiarasu, Igor Sazonov, Si Yong Yeo Computational flow studies in a subject-specific human upper airway using a one-equation turbulence model. Influence of the nasal cavity International Journal for Numerical Methods in Biomedical Engineering, 87(1-5):96–114, 2011 (article)

[BibTex]

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Predicting Articulated Human Motion from Spatial Processes

Soren Hauberg, Kim S. Pedersen

International Journal of Computer Vision, 94, pages: 317-334, Springer Netherlands, 2011 (article)

Publishers site Code Paper site PDF [BibTex]

Soren Hauberg, Kim S. Pedersen Predicting Articulated Human Motion from Spatial Processes International Journal of Computer Vision, 94, pages: 317-334, Springer Netherlands, 2011 (article)

Publishers site Code Paper site PDF [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

Gehler, P., Franz, M. Implicit Wiener Series, Part II: Regularised estimation (148), Max Planck Institute, 2006 (techreport)

pdf [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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Products of “Edge-perts”

Gehler, P., Welling, M.

In Advances in Neural Information Processing Systems 18, pages: 419-426, (Editors: Weiss, Y. and Sch"olkopf, B. and Platt, J.), MIT Press, Cambridge, MA, 2006 (incollection)

pdf [BibTex]

Gehler, P., Welling, M. Products of “Edge-perts” In Advances in Neural Information Processing Systems 18, pages: 419-426, (Editors: Weiss, Y. and Sch"olkopf, B. and Platt, J.), MIT Press, Cambridge, MA, 2006 (incollection)

pdf [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

Wood, F., Black, M. J., Vargas-Irwin, C., Fellows, M., Donoghue, J. P. On the variability of manual spike sorting IEEE Trans. Biomedical Engineering, 51(6):912-918, June 2004 (article)

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]

Wu, W., Black, M. J., Mumford, D., Gao, Y., Bienenstock, E., Donoghue, J. P. Modeling and decoding motor cortical activity using a switching Kalman filter IEEE Trans. Biomedical Engineering, 51(6):933-942, June 2004 (article)

pdf pdf from publisher [BibTex]

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Development of neural motor prostheses for humans

Donoghue, J., Nurmikko, A., Friehs, G., Black, M.

In Advances in Clinical Neurophysiology, (Editors: Hallett, M. and Phillips, L.H. and Schomer, D.L. and Massey, J.M.), Supplements to Clinical Neurophysiology Vol. 57, 2004 (incollection)

pdf [BibTex]

Donoghue, J., Nurmikko, A., Friehs, G., Black, M. Development of neural motor prostheses for humans In Advances in Clinical Neurophysiology, (Editors: Hallett, M. and Phillips, L.H. and Schomer, D.L. and Massey, J.M.), Supplements to Clinical Neurophysiology Vol. 57, 2004 (incollection)

pdf [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.

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1996

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.

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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.

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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)

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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]