Singular foliations with trivial canonical class

This paper describes the structure of singular codimension one foliations with numerically trivial canonical bundle on projective manifolds

Compact leaves of codimension one holomorphic foliations on projective manifolds

This article studies codimension one foliations on projective man-ifolds having a compact leaf (free of singularities). It explores the interplay between Ueda theory (order of flatness of the normal bundle) and the holo-nomy representation (dynamics of the foliation in the transverse direction). We address in particular the following problems: existence of foliation having as a leaf a given hypersurface with topologically torsion normal bundle, global structure of foliations having a compact leaf whose holonomy is abelian (resp. solvable), and factorization results

Phase transitions and symmetry energy in nuclear pasta

Cold and isospin-symmetric nuclear matter at sub-saturation densities is known to form the so-called pasta structures, which, in turn, are known to undergo peculiar phase transitions. Here we investigate if such pastas and their phase changes survive in isospin asymmetric nuclear matter, and whether the symmetry energy of such pasta configurations is connected to the isospin content, the morphology of the pasta and to the phase transitions. We find that indeed pastas are formed in isospin asymmetric systems with proton to neutron ratios of x = 0.3, 0.4 and 0.5, densities in the range of 0.05 fm−3 the morphology of the nuclear matter structure.Fil: Dorso, Claudio Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Frank, Guillermo Alberto. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires. Unidad de Investigación y Desarrollo de las Ingenierías; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: López, Jorge A.. University of Texas at El Paso; Estados Unido

Linear Shape Deformation Models with Local Support Using Graph-based Structured Matrix Factorisation

Representing 3D shape deformations by linear models in high-dimensional space has many applications in computer vision and medical imaging, such as shape-based interpolation or segmentation. Commonly, using Principal Components Analysis a low-dimensional (affine) subspace of the high-dimensional shape space is determined. However, the resulting factors (the most dominant eigenvectors of the covariance matrix) have global support, i.e. changing the coefficient of a single factor deforms the entire shape. In this paper, a method to obtain deformation factors with local support is presented. The benefits of such models include better flexibility and interpretability as well as the possibility of interactively deforming shapes locally. For that, based on a well-grounded theoretical motivation, we formulate a matrix factorisation problem employing sparsity and graph-based regularisation terms. We demonstrate that for brain shapes our method outperforms the state of the art in local support models with respect to generalisation ability and sparse shape reconstruction, whereas for human body shapes our method gives more realistic deformations.Comment: Please cite CVPR 2016 versio

A Solution for Multi-Alignment by Transformation Synchronisation

The alignment of a set of objects by means of transformations plays an important role in computer vision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used. In practice the iterative methods perform well if the relative transformations between any pair of objects are free of noise. However, if only noisy relative transformations are available (e.g. due to missing data or wrong correspondences) the iterative methods may fail. Based on the observation that the underlying noise-free transformations can be retrieved from the null space of a matrix that can directly be obtained from pairwise alignments, this paper presents a novel method for the synchronisation of pairwise transformations such that they are transitively consistent. Simulations demonstrate that for noisy transformations, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.Comment: Accepted for CVPR 2015 (please cite CVPR version