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2012


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An SVD-Based Approach for Ghost Detection and Removal in High Dynamic Range Images

Srikantha, A., Sidibe, D., Meriaudeau, F.

International Conference on Pattern Recognition (ICPR), pages: 380-383, November 2012 (article)

pdf [BibTex]

2012

pdf [BibTex]


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Coupled Action Recognition and Pose Estimation from Multiple Views

Yao, A., Gall, J., van Gool, L.

International Journal of Computer Vision, 100(1):16-37, October 2012 (article)

publisher's site code pdf Project Page Project Page Project Page [BibTex]

publisher's site code pdf Project Page Project Page Project Page [BibTex]


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DRAPE: DRessing Any PErson

Guan, P., Reiss, L., Hirshberg, D., Weiss, A., Black, M. J.

ACM Trans. on Graphics (Proc. SIGGRAPH), 31(4):35:1-35:10, July 2012 (article)

Abstract
We describe a complete system for animating realistic clothing on synthetic bodies of any shape and pose without manual intervention. The key component of the method is a model of clothing called DRAPE (DRessing Any PErson) that is learned from a physics-based simulation of clothing on bodies of different shapes and poses. The DRAPE model has the desirable property of "factoring" clothing deformations due to body shape from those due to pose variation. This factorization provides an approximation to the physical clothing deformation and greatly simplifies clothing synthesis. Given a parameterized model of the human body with known shape and pose parameters, we describe an algorithm that dresses the body with a garment that is customized to fit and possesses realistic wrinkles. DRAPE can be used to dress static bodies or animated sequences with a learned model of the cloth dynamics. Since the method is fully automated, it is appropriate for dressing large numbers of virtual characters of varying shape. The method is significantly more efficient than physical simulation.

YouTube pdf talk Project Page Project Page [BibTex]

YouTube pdf talk Project Page Project Page [BibTex]


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Ghost Detection and Removal for High Dynamic Range Images: Recent Advances

Srikantha, A., Sidib’e, D.

Signal Processing: Image Communication, 27, pages: 650-662, July 2012 (article)

pdf link (url) [BibTex]

pdf link (url) [BibTex]


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Visual Servoing on Unknown Objects

Gratal, X., Romero, J., Bohg, J., Kragic, D.

Mechatronics, 22(4):423-435, Elsevier, June 2012, Visual Servoing \{SI\} (article)

Abstract
We study visual servoing in a framework of detection and grasping of unknown objects. Classically, visual servoing has been used for applications where the object to be servoed on is known to the robot prior to the task execution. In addition, most of the methods concentrate on aligning the robot hand with the object without grasping it. In our work, visual servoing techniques are used as building blocks in a system capable of detecting and grasping unknown objects in natural scenes. We show how different visual servoing techniques facilitate a complete grasping cycle.

Grasping sequence video Offline calibration video Pdf DOI [BibTex]

Grasping sequence video Offline calibration video Pdf DOI [BibTex]


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Visual Orientation and Directional Selectivity Through Thalamic Synchrony

Stanley, G., Jin, J., Wang, Y., Desbordes, G., Wang, Q., Black, M., Alonso, J.

Journal of Neuroscience, 32(26):9073-9088, June 2012 (article)

Abstract
Thalamic neurons respond to visual scenes by generating synchronous spike trains on the timescale of 10–20 ms that are very effective at driving cortical targets. Here we demonstrate that this synchronous activity contains unexpectedly rich information about fundamental properties of visual stimuli. We report that the occurrence of synchronous firing of cat thalamic cells with highly overlapping receptive fields is strongly sensitive to the orientation and the direction of motion of the visual stimulus. We show that this stimulus selectivity is robust, remaining relatively unchanged under different contrasts and temporal frequencies (stimulus velocities). A computational analysis based on an integrate-and-fire model of the direct thalamic input to a layer 4 cortical cell reveals a strong correlation between the degree of thalamic synchrony and the nonlinear relationship between cortical membrane potential and the resultant firing rate. Together, these findings suggest a novel population code in the synchronous firing of neurons in the early visual pathway that could serve as the substrate for establishing cortical representations of the visual scene.

preprint publisher's site Project Page [BibTex]

preprint publisher's site Project Page [BibTex]


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Bilinear Spatiotemporal Basis Models

Akhter, I., Simon, T., Khan, S., Matthews, I., Sheikh, Y.

ACM Transactions on Graphics (TOG), 31(2):17, ACM, April 2012 (article)

Abstract
A variety of dynamic objects, such as faces, bodies, and cloth, are represented in computer graphics as a collection of moving spatial landmarks. Spatiotemporal data is inherent in a number of graphics applications including animation, simulation, and object and camera tracking. The principal modes of variation in the spatial geometry of objects are typically modeled using dimensionality reduction techniques, while concurrently, trajectory representations like splines and autoregressive models are widely used to exploit the temporal regularity of deformation. In this article, we present the bilinear spatiotemporal basis as a model that simultaneously exploits spatial and temporal regularity while maintaining the ability to generalize well to new sequences. This factorization allows the use of analytical, predefined functions to represent temporal variation (e.g., B-Splines or the Discrete Cosine Transform) resulting in efficient model representation and estimation. The model can be interpreted as representing the data as a linear combination of spatiotemporal sequences consisting of shape modes oscillating over time at key frequencies. We apply the bilinear model to natural spatiotemporal phenomena, including face, body, and cloth motion data, and compare it in terms of compaction, generalization ability, predictive precision, and efficiency to existing models. We demonstrate the application of the model to a number of graphics tasks including labeling, gap-filling, denoising, and motion touch-up.

pdf project page link (url) [BibTex]

pdf project page link (url) [BibTex]


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Exploiting pedestrian interaction via global optimization and social behaviors

Leal-Taixé, L., Pons-Moll, G., Rosenhahn, B.

In Theoretic Foundations of Computer Vision: Outdoor and Large-Scale Real-World Scene Analysis, Springer, April 2012 (incollection)

pdf [BibTex]

pdf [BibTex]


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Data-driven Manifolds for Outdoor Motion Capture

Pons-Moll, G., Leal-Taix’e, L., Gall, J., Rosenhahn, B.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 305-328, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

video publisher's site pdf Project Page [BibTex]

video publisher's site pdf Project Page [BibTex]


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A metric for comparing the anthropomorphic motion capability of artificial hands

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

IEEE RAS Transactions on Robotics, TRO, pages: 974-980, 2012 (article)

Publisher site Human Grasping Database Project [BibTex]

Publisher site Human Grasping Database Project [BibTex]


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The Ankyrin 3 (ANK3) Bipolar Disorder Gene Regulates Psychiatric-related Behaviors that are Modulated by Lithium and Stress

Leussis, M., Berry-Scott, E., Saito, M., Jhuang, H., Haan, G., Alkan, O., Luce, C., Madison, J., Sklar, P., Serre, T., Root, D., Petryshen, T.

Biological Psychiatry , 2012 (article)

Prepublication Article Abstract [BibTex]

Prepublication Article Abstract [BibTex]


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Scan-Based Flow Modelling in Human Upper Airways

Perumal Nithiarasu, Igor Sazonov, Si Yong Yeo

In Patient-Specific Modeling in Tomorrow’s Medicine, pages: 241 - 280, 0, (Editors: Amit Gefen), Springer, 2012 (inbook)

[BibTex]

[BibTex]


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An Introduction to Random Forests for Multi-class Object Detection

Gall, J., Razavi, N., van Gool, L.

In Outdoor and Large-Scale Real-World Scene Analysis, 7474, pages: 243-263, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

code code for Hough forest publisher's site pdf Project Page [BibTex]

code code for Hough forest publisher's site pdf Project Page [BibTex]


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Home 3D body scans from noisy image and range data

Weiss, A., Hirshberg, D., Black, M. J.

In Consumer Depth Cameras for Computer Vision: Research Topics and Applications, pages: 99-118, 6, (Editors: Andrea Fossati and Juergen Gall and Helmut Grabner and Xiaofeng Ren and Kurt Konolige), Springer-Verlag, 2012 (incollection)

Project Page [BibTex]

Project Page [BibTex]


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Natural Metrics and Least-Committed Priors for Articulated Tracking

Soren Hauberg, Stefan Sommer, Kim S. Pedersen

Image and Vision Computing, 30(6-7):453-461, Elsevier, 2012 (article)

Publishers site Code PDF [BibTex]

Publishers site Code PDF [BibTex]

2009


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Fields of Experts

Roth, S., Black, M. J.

International Journal of Computer Vision (IJCV), 82(2):205-29, April 2009 (article)

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

pdf pdf from publisher [BibTex]

2009

pdf pdf from publisher [BibTex]


no image
An introduction to Kernel Learning Algorithms

Gehler, P., Schölkopf, B.

In Kernel Methods for Remote Sensing Data Analysis, pages: 25-48, 2, (Editors: Gustavo Camps-Valls and Lorenzo Bruzzone), Wiley, New York, NY, USA, 2009 (inbook)

Abstract
Kernel learning algorithms are currently becoming a standard tool in the area of machine learning and pattern recognition. In this chapter we review the fundamental theory of kernel learning. As the basic building block we introduce the kernel function, which provides an elegant and general way to compare possibly very complex objects. We then review the concept of a reproducing kernel Hilbert space and state the representer theorem. Finally we give an overview of the most prominent algorithms, which are support vector classification and regression, Gaussian Processes and kernel principal analysis. With multiple kernel learning and structured output prediction we also introduce some more recent advancements in the field.

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Visual Object Discovery

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

In Object Categorization: Computer and Human Vision Perspectives, pages: 301-323, (Editors: S. J. Dickinson, A. Leonardis, B. Schiele, M.J. Tarr), Cambridge University Press, 2009 (inbook)

link (url) [BibTex]

link (url) [BibTex]


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Left Ventricular Regional Wall Curvedness and Wall Stress in Patients with Ischemic Dilated Cardiomyopathy

Liang Zhong, Yi Su, Si Yong Yeo, Ru San Tan Dhanjoo Ghista, Ghassan Kassab

American Journal of Physiology – Heart and Circulatory Physiology, 296(3):H573-84, 2009 (article)

Abstract
Geometric remodeling of the left ventricle (LV) after myocardial infarction is associated with changes in myocardial wall stress. The objective of this study was to determine the regional curvatures and wall stress based on three-dimensional (3-D) reconstructions of the LV using MRI. Ten patients with ischemic dilated cardiomyopathy (IDCM) and 10 normal subjects underwent MRI scan. The IDCM patients also underwent delayed gadolinium-enhancement imaging to delineate the extent of myocardial infarct. Regional curvedness, local radii of curvature, and wall thickness were calculated. The percent curvedness change between end diastole and end systole was also calculated. In normal heart, a short- and long-axis two-dimensional analysis showed a 41 +/- 11% and 45 +/- 12% increase of the mean of peak systolic wall stress between basal and apical sections, respectively. However, 3-D analysis showed no significant difference in peak systolic wall stress from basal and apical sections (P = 0.298, ANOVA). LV shape differed between IDCM patients and normal subjects in several ways: LV shape was more spherical (sphericity index = 0.62 +/- 0.08 vs. 0.52 +/- 0.06, P < 0.05), curvedness at end diastole (mean for 16 segments = 0.034 +/- 0.0056 vs. 0.040 +/- 0.0071 mm(-1), P < 0.001) and end systole (mean for 16 segments = 0.037 +/- 0.0068 vs. 0.067 +/- 0.020 mm(-1), P < 0.001) was affected by infarction, and peak systolic wall stress was significantly increased at each segment in IDCM patients. The 3-D quantification of regional wall stress by cardiac MRI provides more precise evaluation of cardiac mechanics. Identification of regional curvedness and wall stresses helps delineate the mechanisms of LV remodeling in IDCM and may help guide therapeutic LV restoration.

[BibTex]

[BibTex]


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A Curvature-Based Approach for Left Ventricular Shape Analysis from Cardiac Magnetic Resonance Imaging

Si Yong Yeo, Liang Zhong, Yi Su, Ru San Tan, Dhanjoo Ghista

Medical & Biological Engineering & Computing, 47(3):313-322, 2009 (article)

Abstract
It is believed that left ventricular (LV) regional shape is indicative of LV regional function, and cardiac pathologies are often associated with regional alterations in ventricular shape. In this article, we present a set of procedures for evaluating regional LV surface shape from anatomically accurate models reconstructed from cardiac magnetic resonance (MR) images. LV surface curvatures are computed using local surface fitting method, which enables us to assess regional LV shape and its variation. Comparisons are made between normal and diseased hearts. It is illustrated that LV surface curvatures at different regions of the normal heart are higher than those of the diseased heart. Also, the normal heart experiences a larger change in regional curvedness during contraction than the diseased heart. It is believed that with a wide range of dataset being evaluated, this approach will provide a new and efficient way of quantifying LV regional function.

link (url) [BibTex]

link (url) [BibTex]

2007


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Learning static Gestalt laws through dynamic experience

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

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

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

link (url) DOI [BibTex]

2007

link (url) DOI [BibTex]


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Neuromotor prosthesis development

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

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

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

pdf [BibTex]

pdf [BibTex]


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On the spatial statistics of optical flow

Roth, S., Black, M. J.

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

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

pdf preprint pdf from publisher [BibTex]

pdf preprint pdf from publisher [BibTex]


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

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

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

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

pdf preprint pdf from publisher DOI [BibTex]

pdf preprint pdf from publisher DOI [BibTex]


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Probabilistically modeling and decoding neural population activity in motor cortex

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

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

pdf [BibTex]

pdf [BibTex]

2005


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Representing cyclic human motion using functional analysis

Ormoneit, D., Black, M. J., Hastie, T., Kjellström, H.

Image and Vision Computing, 23(14):1264-1276, December 2005 (article)

Abstract
We present a robust automatic method for modeling cyclic 3D human motion such as walking using motion-capture data. The pose of the body is represented by a time-series of joint angles which are automatically segmented into a sequence of motion cycles. The mean and the principal components of these cycles are computed using a new algorithm that enforces smooth transitions between the cycles by operating in the Fourier domain. Key to this method is its ability to automatically deal with noise and missing data. A learned walking model is then exploited for Bayesian tracking of 3D human motion.

pdf pdf from publisher DOI [BibTex]

2005

pdf pdf from publisher DOI [BibTex]