Application of the Fisher-Rao metric to ellipse detection

The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold corresponds to an ellipse in the image. The parameter space becomes a Riemannian manifold under a Fisher-Rao metric, which is derived from a Gaussian model for the blurring of ellipses in the image. Two points in the parameter space are close together under the Fisher-Rao metric if the corresponding ellipses are close together in the image. The Fisher-Rao metric is accurately approximated by a simpler metric under the assumption that the blurring is small compared with the sizes of the ellipses under consideration. It is shown that the parameter space for the ellipses in the image has a finite volume under the approximation to the Fisher-Rao metric. As a consequence the parameter space can be replaced, for the purpose of ellipse detection, by a finite set of points sampled from it. An efficient algorithm for sampling the parameter space is described. The algorithm uses the fact that the approximating metric is flat, and therefore locally Euclidean, on each three dimensional family of ellipses with a fixed orientation and a fixed eccentricity. Once the sample points have been obtained, ellipses are detected in a given image by checking each sample point in turn to see if the corresponding ellipse is supported by the nearby image pixel values. The resulting algorithm for ellipse detection is implemented. A multiresolution version of the algorithm is also implemented. The experimental results suggest that ellipses can be reliably detected in a given low resolution image and that the number of false detections can be reduced using the multiresolution algorithm

Granular Pressure and the Thickness of a Layer Jamming on a Rough Incline

Dense granular media have a compaction between the random loose and random close packings. For these dense media the concept of a granular pressure depending on compaction is not unanimously accepted because they are often in a "frozen" state which prevents them to explore all their possible microstates, a necessary condition for defining a pressure and a compressibility unambiguously. While periodic tapping or cyclic fluidization have already being used for that exploration, we here suggest that a succession of flowing states with velocities slowly decreasing down to zero can also be used for that purpose. And we propose to deduce the pressure in \emph{dense and flowing} granular media from experiments measuring the thickness of the granular layer that remains on a rough incline just after the flow has stopped.Comment: 10 pages, 2 figure

Note on a Micropolar Gas-Kinetic Theory

The micropolar fluid mechanics and its transport coefficients are derived from the linearized Boltzmann equation of rotating particles. In the dilute limit, as expected, transport coefficients relating to microrotation are not important, but the results are useful for the description of collisional granular flow on an inclined slope. (This paper will be published in Traffic and Granular Flow 2001 edited by Y.Sugiyama and D. E. Wolf (Springer))Comment: 15 pages, 0 figure. To be published in Traffic and Granular Flow 2001 edited by Y.Sugiyama and D. E. Wolf (Springer

Toxoplasma-Induced Hypermigration of Primary Cortical Microglia Implicates GABAergic Signaling

Toxoplasma gondii is a widespread obligate intracellular parasite that causes chronic infection and life-threatening acute infection in the central nervous system. Previous work identified Toxoplasma-infected microglia and astrocytes during reactivated infections in mice, indicating an implication of glial cells in acute toxoplasmic encephalitis. However, the mechanisms leading to the spread of Toxoplasma in the brain parenchyma remain unknown. Here, we report that, shortly after invasion by T. gondii tachyzoites, parasitized microglia, but not parasitized astrocytes, undergo rapid morphological changes and exhibit dramatically enhanced migration in 2-dimensional and 3-dimensional matrix confinements. Interestingly, primary microglia secreted the neurotransmitter γ-aminobutyric acid (GABA) in the supernatant as a consequence of T. gondii infection but not upon stimulation with LPS or heat-inactivated T. gondii. Further, microglia transcriptionally expressed components of the GABAergic machinery, including GABA-A receptor subunits, regulatory molecules and voltage-dependent calcium channels (VDCCs). Further, their transcriptional expression was modulated by challenge with T. gondii. Transcriptional analysis indicated that GABA was synthesized via both, the conventional pathway (glutamate decarboxylases GAD65 and GAD67) and a more recently characterized alternative pathway (aldehyde dehydrogenases ALDH2 and ALDH1a1). Pharmacological inhibitors targeting GABA synthesis, GABA-A receptors, GABA-A regulators and VDCC signaling inhibited Toxoplasma-induced hypermotility of microglia. Altogether, we show that primary microglia express a GABAergic machinery and that T. gondii induces hypermigration of microglia in a GABA-dependent fashion. We hypothesize that migratory activation of parasitized microglia by Toxoplasma may promote parasite dissemination in the brain parenchyma

Stress and Strain in Flat Piling of Disks

We have created a flat piling of disks in a numerical experiment using the Distinct Element Method (DEM) by depositing them under gravity. In the resulting pile, we then measured increments in stress and strain that were associated with a small decrease in gravity. We first describe the stress in terms of the strain using isotropic elasticity theory. Then, from a micro-mechanical view point, we calculate the relation between the stress and strain using the mean strain assumption. We compare the predicted values of Young's modulus and Poisson's ratio with those that were measured in the numerical experiment.Comment: 9 pages, 1 table, 8 figures, and 2 pages for captions of figure

Long-time asymptotics of the long-range Emch-Radin model

The long-time asymptotic behavior is studied for a long-range variant of the Emch-Radin model of interacting spins. We derive upper and lower bounds on the expectation values of a class of observables. We prove analytically that the time scale at which the system relaxes to equilibrium diverges with the system size N, displaying quasistationary nonequilibrium behavior. This finding implies that, for large enough N, equilibration will not be observed in an experiment of finite duration.Comment: 12 pages, 2 figures. Compared to the published version, a 1/2 has been corrected in Eq. (9) and subsequent equations; the modifications are insubstantial and leave the main results of the article unaltered. arXiv admin note: substantial text overlap with arXiv:1103.083

A Fisher-Rao metric for paracatadioptric images of lines

In a central paracatadioptric imaging system a perspective camera takes an image of a scene reflected in a paraboloidal mirror. A 360° field of view is obtained, but the image is severely distorted. In particular, straight lines in the scene project to circles in the image. These distortions make it diffcult to detect projected lines using standard image processing algorithms. The distortions are removed using a Fisher-Rao metric which is defined on the space of projected lines in the paracatadioptric image. The space of projected lines is divided into subsets such that on each subset the Fisher-Rao metric is closely approximated by the Euclidean metric. Each subset is sampled at the vertices of a square grid and values are assigned to the sampled points using an adaptation of the trace transform. The result is a set of digital images to which standard image processing algorithms can be applied. The effectiveness of this approach to line detection is illustrated using two algorithms, both of which are based on the Sobel edge operator. The task of line detection is reduced to the task of finding isolated peaks in a Sobel image. An experimental comparison is made between these two algorithms and third algorithm taken from the literature and based on the Hough transform

A QCQP Approach to Triangulation

Triangulation of a three-dimensional point from at least two noisy 2-D images can be formulated as a quadratically constrained quadratic program. We propose an algorithm to extract candidate solutions to this problem from its semidefinite programming relaxations. We then describe a sufficient condition and a polynomial time test for certifying when such a solution is optimal. This test has no false positives. Experiments indicate that false negatives are rare, and the algorithm has excellent performance in practice. We explain this phenomenon in terms of the geometry of the triangulation problem.Comment: 14 pages, to appear in the proceedings of the 12th European Conference of Computer Vision, Firenze, Italy, 7-13 October 201

Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces

Charting cortical growth trajectories is of paramount importance for understanding brain development. However, such analysis necessitates the collection of longitudinal data, which can be challenging due to subject dropouts and failed scans. In this paper, we will introduce a method for longitudinal prediction of cortical surfaces using a spatial graph convolutional neural network (GCNN), which extends conventional CNNs from Euclidean to curved manifolds. The proposed method is designed to model the cortical growth trajectories and jointly predict inner and outer cortical surfaces at multiple time points. Adopting a binary flag in loss calculation to deal with missing data, we fully utilize all available cortical surfaces for training our deep learning model, without requiring a complete collection of longitudinal data. Predicting the surfaces directly allows cortical attributes such as cortical thickness, curvature, and convexity to be computed for subsequent analysis. We will demonstrate with experimental results that our method is capable of capturing the nonlinearity of spatiotemporal cortical growth patterns and can predict cortical surfaces with improved accuracy.Comment: Accepted as oral presentation at IPMI 201

Macro deformation and micro structure of 3D granular assemblies subjected to rotation of principal stress axes

This paper presents a numerical investigation on the behavior of three dimensional granular materials during continuous rotation of principal stress axes using the discrete element method. A dense specimen has been prepared as a representative element using the deposition method and subjected to stress rotation at different deviatoric stress levels. Significant plastic deformation has been observed despite that the principal stresses are kept constant. This contradicts the classical plasticity theory, but is in agreement with previous laboratory observations on sand and glass beads. Typical deformation characteristics, including volume contraction, deformation non-coaxiality, have been successfully reproduced. After a larger number of rotational cycles, the sample approaches the ultimate state with constant void ratio and follows a periodic strain path. The internal structure anisotropy has been quantified in terms of the contact-based fabric tensor. Rotation of principal stress axes densifies the packing, and leads to the increase in coordination numbers. A cyclic rotation in material anisotropy has been observed. The larger the stress ratio, the structure becomes more anisotropic. A larger fabric trajectory suggests more significant structure re-organization when rotating and explains the occurrence of more significant strain rate. The trajectory of the contact-normal based fabric is not centered in the origin, due to the anisotropy in particle orientation generated during sample generation which is persistent throughout the shearing process. The sample sheared at a lower intermediate principal stress ratio (b=0.0) (b=0.0) has been observed to approach a smaller strain trajectory as compared to the case b=0.5 b=0.5 , consistent with a smaller fabric trajectory and less significant structural re-organisation. It also experiences less volume contraction with the out-of plane strain component being dilative