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2011


Dorsal Stream: From Algorithm to Neuroscience
Dorsal Stream: From Algorithm to Neuroscience

Jhuang, H.

PhD Thesis, MIT, 2011 (techreport)

pdf [BibTex]


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

[BibTex]


 Geometrically Induced Force Interaction for Three-Dimensional Deformable Models
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]

[BibTex]


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

[BibTex]


Predicting Articulated Human Motion from Spatial Processes
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]

Publishers site Code Paper site PDF [BibTex]

2009


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ISocRob-MSL 2009 Team Description Paper for Middle Sized League

Lima, P., Santos, J., Estilita, J., Barbosa, M., Ahmad, A., Carreira, J.

13th Annual RoboCup International Symposium 2009, July 2009 (techreport)

Abstract
This paper describes the status of the ISocRob MSL roboticsoccer team as required by the RoboCup 2009 qualification procedures.Since its previous participation in RoboCup, the ISocRob team has car-ried out significant developments in various topics, the most relevantof which are presented here. These include self-localization, 3D objecttracking and cooperative object localization, motion control and rela-tional behaviors. A brief description of the hardware of the ISocRobrobots and of the software architecture adopted by the team is also in-cluded.

[BibTex]

2009

[BibTex]


Fields of Experts
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]

pdf pdf from publisher [BibTex]


Automatic recognition of rodent behavior: A tool for systematic phenotypic analysis
Automatic recognition of rodent behavior: A tool for systematic phenotypic analysis

Serre, T.*, Jhuang, H*., Garrote, E., Poggio, T., Steele, A.

CBCL paper #283/MIT-CSAIL-TR #2009-052., MIT, 2009 (techreport)

pdf [BibTex]

pdf [BibTex]


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


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

2006


Implicit Wiener Series, Part II: Regularised estimation
Implicit Wiener Series, Part II: Regularised estimation

Gehler, P., Franz, M.

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

pdf [BibTex]

2006


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


Bayesian population decoding of motor cortical activity using a {Kalman} filter
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]

2003


Learning the statistics of people in images and video
Learning the statistics of people in images and video

Sidenbladh, H., Black, M. J.

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

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

pdf pdf from publisher code DOI [BibTex]

2003

pdf pdf from publisher code DOI [BibTex]


A framework for robust subspace learning
A framework for robust subspace learning

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

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

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

pdf code pdf from publisher Project Page [BibTex]

pdf code pdf from publisher Project Page [BibTex]


Guest editorial: Computational vision at {Brown}
Guest editorial: Computational vision at Brown

Black, M. J., Kimia, B.

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

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


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

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

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

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

pdf [BibTex]

pdf [BibTex]