fuzzy edge detection for omnidirectional images the use of omnidirectional vision has increased during these past years it provides a very large field of view nevertheless omnidirectional images contain significant radial distortions and conventional image processing is not adapted to these specific images this paper presents an edge detector adapted to the image geometry fuzzy sets will be used to take into account all imprecisions introduced by the sampling process the prewitt filter applied to omnidirectional image will be studied to illustrate this paper

correspondence free structure from motion we present a novel approach for the estimation of 3d motion directly from two images using the radon transform the feasibility of any camera motion is computed by integrating over all feature pairs that satisfy the epipolar constraint this integration is equivalent to taking the inner product of a similarity function on feature pairs with a dirac function embedding the epipolar constraint the maxima in this five dimensional motion space will correspond to compatible rigid motions the main novelty is in the realization that the radon transform is a filtering operator if we assume that the similarity and dirac functions are defined on spheres and the epipolar constraint is a group action of rotations on spheres then the radon transform is a correlation integral we propose a new algorithm to compute this integral from the spherical fourier transform of the similarity and dirac functions generating the similarity function now becomes a preprocessing step which reduces the complexity of the radon computation by a factor equal to the number of feature pairs processed the strength of the algorithm is in avoiding a commitment to correspondences thus being robust to erroneous feature detection outliers and multiple motions

local and cluster critical dynamics of the 3d random site ising model abstract we present the results of monte carlo simulations for the critical dynamics of the three dimensional site diluted quenched ising model three different dynamics are considered these correspond to the local update metropolis scheme as well as to the swendsen wang and wolff cluster algorithms the lattice sizes of l 10 96 are analysed by a finite size scaling technique the site dilution concentration p 0 85 was chosen to minimize the correction to scaling effects we calculate numerical values of the dynamical critical exponents for the integrated and exponential autocorrelation times for energy and magnetization as expected cluster algorithms are characterized by lower values of dynamical critical exponent than the local one also in the case of dilution critical slowing down is more pronounced for the metropolis algorithm however the striking feature of our estimates is that they suggest that dilution leads to decrease of the dynamical critical exponent for the cluster algorithms this phenomenon is quite opposite to the local dynamics where dilution enhances critical slowing down

cellular automata as microcanonical simulators the deterministic q2r cellular automation has been tested by many authors as a fast algorithm to simulate the ising model in the microcanonical ensemble however the magnetic susceptibility curve measured from the fluctuations of the magnetization is found to be far below the expected results inside the ordered ising phase the non ergodicity degree of this automaton seems to be inadequate to simulate the ising dynamics in this work the authors introduce two modified automata and test their performance for the square lattice for the first one they found improved results concerning the ising transition for the second modified automaton the ising transition does not occur the magnetization vanishing even for energies far below the normal critical threshold on the other hand another transition appears at a different critical energy value that seems to be the same as that of the periodic chaotic transition already observed in the normal q2r dynamics the critical indices of this new transition are measured from finite size scaling the results indicating that it is at the same universality class as the ising transition

lyapunov based range identification for paracatadioptric systems many applications require the interpretation of the euclidean coordinates of features of a 3 d object through 2 d images in this paper the relative range and the euclidean coordinates of an object or camera undergoing general affine motion are determined for paracatadioptric imaging systems via a nonlinear observer the nonlinear observer asymptotically determines the range information provided that the motion parameters are known the observer is developed through a lyapunov based design and stability analysis and simulation results are provided that illustrate the performance of the state estimator the contributions of this paper are that the developed observer 1 can be applied to both affine and nonaffine systems 2 can be used for both the fixed and moving camera configurations 3 is continuous and 4 yields an asymptotic result

catadioptric camera calibration using geometric invariants central catadioptric cameras are imaging devices that use mirrors to enhance the field of view while preserving a single effective viewpoint in this paper we propose a novel method for the calibration of central catadioptric cameras using geometric invariants lines and spheres in space are all projected into conics in the catadioptric image plane we prove that the projection of a line can provide three invariants whereas the projection of a sphere can only provide two from these invariants constraint equations for the intrinsic parameters of catadioptric camera are derived therefore there are two kinds of variants of this novel method the first one uses projections of lines and the second one uses projections of spheres in general the projections of two lines or three spheres are sufficient to achieve catadioptric camera calibration one important conclusion in this paper is that the method based on projections of spheres is more robust and has higher accuracy than that based on projections of lines the performances of our method are demonstrated by both the results of simulations and experiments with real images

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 difficult 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

space time finite elements for the analysis of transient wave propagation in unbounded layered media a new method is proposed for the analysis of transient wave propagation in a layered stratum it makes use of the separation of variables technique and reduces the spatial dimension of analysis to one the resulting system of hyperbolic partial differential equations is solved via element by element computations based on a space time galerkin finite element method this method is shown to be more efficient than the methods based on convolution numerical examples are presented to illustrate the effectiveness of the method current limitations and possible extensions are also discussed

rotation recovery from spherical images without correspondences this paper addresses the problem of rotation estimation directly from images defined on the sphere and without correspondence the method is particularly useful for the alignment of large rotations and has potential impact on 3d shape alignment the foundation of the method lies in the fact that the spherical harmonic coefficients undergo a unitary mapping when the original image is rotated the correlation between two images is a function of rotations and we show that it has an so 3 fourier transform equal to the pointwise product of spherical harmonic coefficients of the original images the resolution of the rotation space depends on the bandwidth we choose for the harmonic expansion and the rotation estimate is found through a direct search in this 3d discretized space a refinement of the rotation estimate can be obtained from the conservation of harmonic coefficients in the rotational shift theorem a novel decoupling of the shift theorem with respect to the euler angles is presented and exploited in an iterative scheme to refine the initial rotation estimates experiments show the suitability of the method for large rotations and the dependence of the method on bandwidth and the choice of the spherical harmonic coefficients

fast geodesic active fields for image registration based on splitting and augmented lagrangian approaches in this paper we present an efficient numerical scheme for the recently introduced geodesic active fields gaf framework for geometric image registration this framework considers the registration task as a weighted minimal surface problem hence the data term and the regularization term are combined through multiplication in a single parametrization invariant and geometric cost functional the multiplicative coupling provides an intrinsic spatially varying and data dependent tuning of the regularization strength and the parametrization invariance allows working with images of nonflat geometry generally defined on any smoothly parametrizable manifold the resulting energy minimizing flow however has poor numerical properties here we provide an efficient numerical scheme that uses a splitting approach data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented lagrangian approach our approach is more flexible than standard gaussian regularization since one can interpolate freely between isotropic gaussian and anisotropic tv like smoothing in this paper we compare the geodesic active fields method with the popular demons method and three more recent state of the art algorithms nl optical flow mrf image registration and landmark enhanced large displacement optical flow thus we can show the advantages of the proposed fastgaf method it compares favorably against demons both in terms of registration speed and quality over the range of example applications it also consistently produces results not far from more dedicated state of the art methods illustrating the flexibility of the proposed framework

scale invariant features and polar descriptors in omnidirectional imaging we propose a method to compute scale invariant features in omnidirectional images we present a formulation based on the riemannian geometry for the definition of differential operators on non euclidian manifolds that adapt to the mirror and lens structures in omnidirectional imaging these operators lead to a scale space analysis that preserves the geometry of the visual information in omnidirectional images we then build a novel scale invariant feature detection framework for omnidirectional images that can be mapped on the sphere we further present a new descriptor and feature matching solution for these omnidirectional images the descriptor builds on the log polar planar descriptors and adapts the descriptor computation to the specific geometry and the nonuniform sampling density of omnidirectional images we also propose a rotation invariant matching method that eliminates the orientation computation during the feature detection phase and thus decreases the computational complexity experimental results demonstrate that the new feature computation method combined with the adapted descriptors offers promising detection and matching performance i e it improves on the common scale invariant feature transform sift features computed on the unwrapped omnidirectional images as well as spherical sift features finally we show that the proposed framework also permits to match features between images with different native geometry

scale invariant feature transform on the sphere theory and applications a sift algorithm in spherical coordinates for omnidirectional images is proposed this algorithm can generate two types of local descriptors local spherical descriptors and local planar descriptors with the first ones point matching between two omnidirectional images can be performed and with the second ones the same matching process can be done but between omnidirectional and planar images furthermore a planar to spherical mapping is introduced and an algorithm for its estimation is given this mapping allows to extract objects from an omnidirectional image given their sift descriptors in a planar image several experiments confirming the promising and accurate performance of the system are conducted

a multiscale discontinuous galerkin method with the computational structure of a continuous galerkin method proliferation of degrees of freedom has plagued discontinuous galerkin methodology from its inception over 30 years ago this paper develops a new computational formulation that combines the advantages of discontinuous galerkin methods with the data structure of their continuous galerkin counterparts the new method uses local element wise problems to project a continuous finite element space into a given discontinuous space and then applies a discontinuous galerkin formulation the projection leads to parameterization of the discontinuous degrees of freedom by their continuous counterparts and has a variational multiscale interpretation this significantly reduces the computational burden and at the same time little or no degradation of the solution occurs in fact the new method produces improved solutions compared with the traditional discontinuous galerkin method in some situations

optimal estimation and detection in homogeneous spaces this paper presents estimation and detection techniques in homogeneous spaces that are optimal under the squared error loss function the data is collected on a manifold which forms a homogeneous space under the transitive action of a compact lie group signal estimation problems are addressed by formulating wiener hopf equations for homogeneous spaces the coefficient functions of these equations are the signal correlations which are assumed to be known the resulting coupled integral equations on the manifold are converted to wiener hopf convolutional integral equations on the group these are solved using the peter weyl theory of fourier transform on compact lie groups the computational complexity of this algorithm is reduced using the bi invariance of the correlations with respect to a stabilizer subgroup the theory of matched filtering for isotropic signal fields is developed for signal classification where given a set of template signals on the manifold and a noisy test signal the objective is to optimally detect the template buried in the test signal this is accomplished by designing a filter on the manifold that maximizes the signal to noise ratio snr of the filtered output an expression for the snr is obtained as a ratio of quadratic forms expressed as haar integrals over the transformation group these integrals are expressed in the fourier domain as infinite sums over the irreducible representations simplification of these sums is achieved by invariance properties of the signal function and the noise correlation function the wiener filter and matched filter are developed for an abstract homogeneous space and then specialized to the case of spherical signals under the action of the rotation group applications of these algorithms to denoising of 3d surface data visual navigation with omnidirectional camera and detection of compact embedded objects in the stochastic background are discussed with experimental results

reciprocal absorbing boundary condition for the time domain numerical analysis of wave motion in unbounded layered media a global absorbing boundary condition is introduced for the time domain numerical analysis of wave motion in unbounded layered media this condition is obtained by applying the reciprocity theorem for linearly viscoelastic media example problems are solved towards evaluation of the accuracy and effectiveness of the approach developed in this work

some observations on time domain and frequency domain boundary elements the numerical solution of problems in elastodynamics involving infinite media calls for the use of discrete techniques such as the boundary element method and the finite element method these techniques can in turn be formulated in the time or frequency domains and have each relative merits and drawbacks this paper presents a comparative study of the accuracy and limitations of three different implementations of these methods the problem studied is that of transient loads on the surface of homogeneous elastic halfspaces and of finite depth strata in each case the response is computed first for an uninterrupted continuous medium and then for a medium that includes a trench or cavity three independent computer programs were used that incorporated the following methods i frequency domain boundary element method fd bem using a discrete fundamental solution ii time domain boundary element method td bem using an analytical fundamental solution and iii a coupled time domain boundary element finite element model bem fem it is found that for convex domains halfspace or stratum without a trench the three independent implementations are in excellent agreement while for non convex domains trench in the path of the waves numerical errors associated with non causal behaviour become evident in some cases

intrinsic parameter calibration procedure for a high distortion fish eye lens camera with distortion model and accuracy estimation this paper presents a calibration procedure for a fish eye lens a high distortion lens mounted on a ccd tv camera the method is designed to account for the differences in images acquired via a distortion free lens camera setup and the images obtained by a fish eye lens camera the calibration procedure essentially defines a mapping between points in the world coordinate system and their corresponding point locations in the image plane this step is important for applications in computer vision which involve quantitative measurements the objective of this mapping is to estimate the internal parameters of the camera including the effective focal length one pixel width on the image plane image distortion center and distortion coefficients the number of parameters to be calibrated is reduced by using a calibration pattern with equally spaced dots and assuming a pin hole model camera behavior for the image center thus assuming negligible distortion at the image distortion center our method employs a non linear transformation between points in the world coordinate system and their corresponding location on the image plane a lagrangian minimization method is used to determine the coefficients of the transformation the validity and effectiveness of our calibration and distortion correction procedure are confirmed by application of this procedure on real images

variable structuring element based fuzzy morphological operations for single viewpoint omnidirectional images morphological tools can provide transformations suitable for real projective images but the camera and objects to be analyzed have to be positioned in such a manner that a regular mesh on the objects projects a regular mesh on the image a morphological modification of the image is thus the projection of an equivalent operation on the object otherwise due to perspective effects a morphological operation on the image is not the projection of an equivalent operation on the objects to be analyzed with catadioptric omnidirectional images it is almost impossible to place the sensor such that a regular mesh on the scene projects a regular mesh on the image nevertheless with proper calibration of a central catadioptric system the projection of a regular structuring element in a scene can be determined for each point on the image the aim of this paper is to present new morphological operators that use this projective property these operators make use of a structuring element of varying shape since this varying shape cannot be represented as a binary union of pixels we propose to use a fuzzy extension of the classical gray level morphology to account for this phenomenon this fuzzy extension is performed via fuzzy integrals

catadioptric projective geometry catadioptric sensors are devices which utilize mirrors and lenses to form a projection onto the image plane of a camera central catadioptric sensors are the class of these devices having a single effective viewpoint in this paper we propose a unifying model for the projective geometry induced by these devices and we study its properties as well as its practical implications we show that a central catadioptric projection is equivalent to a two step mapping via the sphere the second step is equivalent to a stereographic projection in the case of parabolic mirrors conventional lens based perspective cameras are also central catadioptric devices with a virtual planar mirror and are thus covered by the unifying model we prove that for each catadioptric projection there exists a dual catadioptric projection based on the duality between points and line images conics it turns out that planar and parabolic mirrors build a dual catadioptric projection pair as a practical example we describe a procedure to estimate focal length and image center from a single view of lines in arbitrary position for a parabolic catadioptric system

paracatadioptric camera calibration catadioptric sensors refer to the combination of lens based devices and reflective surfaces these systems are useful because they may have a field of view which is greater than hemispherical providing the ability to simultaneously view in any direction configurations which have a unique effective viewpoint are of primary interest among these is the case where the reflective surface is a parabolic mirror and the camera is such that it induces an orthographic projection and which we call paracatadioptric we present an algorithm for the calibration of such a device using only the images of lines in space in fact we show that we may obtain all of the intrinsic parameters from the images of only three lines and that this is possible without any metric information we propose a closed form solution for focal length image center and aspect ratio for skewless cameras and a polynomial root solution in the presence of skew we also give a method for determining the orientation of a plane containing two sets of parallel lines from one uncalibrated view such an orientation recovery enables a rectification which is impossible to achieve in the case of a single uncalibrated view taken by a conventional camera we study the performance of the algorithm in simulated setups and compare results on real images with an approach based on the image of the mirror s bounding circle

characteristics methods for transient analysis of wave propagation in unbounded media a method based on characteristics was developed recently for the analysis of wave propagation in unbounded layered media 7 in this paper the method is extended to problems involving spherical and cylindrical computational boundaries the procedure resulting from straightforward extension of the method meets with several difficulties in stability and accuracy modifications based on radial scaling and upwinding are applied to circumvent these difficulties the resulting boundary conditions have all the properties desired in an artificial boundary condition numerical experiments are presented to illustrate the effectiveness of the procedure

geometry based distributed scene representation with omnidirectional vision sensors this paper addresses the problem of efficient representation of scenes captured by distributed omnidirectional vision sensors we propose a novel geometric model to describe the correlation between different views of a 3 d scene we first approximate the camera images by sparse expansions over a dictionary of geometric atoms since the most important visual features are likely to be equivalently dominant in images from multiple cameras we model the correlation between corresponding features in different views by local geometric transforms for the particular case of omnidirectional images we define the multiview transforms between corresponding features based on shape and epipolar geometry constraints we apply this geometric framework in the design of a distributed coding scheme with side information which builds an efficient representation of the scene without communication between cameras the wyner ziv encoder partitions the dictionary into cosets of dissimilar atoms with respect to shape and position in the image the joint decoder then determines pairwise correspondences between atoms in the reference image and atoms in the cosets of the wyner ziv image in order to identify the most likely atoms to decode under epipolar geometry constraints experiments demonstrate that the proposed method leads to reliable estimation of the geometric transforms between views in particular the distributed coding scheme offers similar rate distortion performance as joint encoding at low bit rate and outperforms methods based on independent decoding of the different images

identical projective geometric properties of central catadioptric line images and sphere images with applications to calibration central catadioptric cameras are imaging devices that use mirrors to enhance the field of view while preserving a single effective viewpoint lines and spheres in space are all projected into conics in the central catadioptric image planes and such conics are called line images and sphere images respectively we discovered that there exists an imaginary conic in the central catadioptric image planes defined as the modified image of the absolute conic miac and by utilizing the miac the novel identical projective geometric properties of line images and sphere images may be exploited each line image or each sphere image is double contact with the miac which is an analogy of the discovery in pinhole camera that the image of the absolute conic iac is double contact with sphere images note that the iac also exists in the central catadioptric image plane but it does not have the double contact properties with line images or sphere images this is the main reason to propose the miac from these geometric properties with the miac two linear calibration methods for central catadioptric cameras using sphere images as well as using line images are proposed in the same framework note that there are many linear approaches to central catadioptric camera calibration using line images it seems that to use the properties that line images are tangent to the miac only leads to an alternative geometric construction for calibration however for sphere images there are only some nonlinear calibration methods in literature therefore to propose linear methods for sphere images may be the main contribution of this paper our new algorithms have been tested in extensive experiments with respect to noise sensitivity

a discontinuous galerkin method for transient analysis of wave propagation in unbounded domains a technique based on the discontinuous galerkin finite element method is developed and applied to the derivation of an absorbing boundary condition for the analysis of transient wave propagation the condition is exact in that only discretization error is involved furthermore the computational cost associated with use of the condition is an order of magnitude lower than for conditions based on green functions the time stepping scheme resulting from an implicit method in conjunction with this boundary condition appears to be unconditionally stable

an efficient numerical algorithm for transient analysis of exterior scalar wave propagation in a homogeneous layer abstract in this paper a computationally efficient alternative for the analysis of transient wave propagation in an infinite layer is presented the new method is based on a simple cell centered characteristic finite difference technique this approach can be used in place of the existing methods based on closed form green s functions as it would save considerable computational time and storage numerical examples are presented to illustrate the performance of the method some guidelines are suggested to further increase the efficiency of the proposed method

a discontinuoushpfinite element method for diffusion problems we present an extension of the discontinuous galerkin method which is applicable to the numerical solution of diffusion problems the method involves a weak imposition of continuity conditions on the solution values and on fluxes across interelement boundaries within each element arbitrary spectral approximations can be constructed with different orderspin each element we demonstrate that the method is elementwise conservative a property uncharacteristic of high order finite elements for clarity we focus on a model class of linear second order boundary value problems and we developpriorierror estimates convergence proofs and stability estimates the results of numerical experiments onh andp convergence rates for representative two dimensional problems suggest that the method is robust and capable of delivering exponential rates of convergence

joint registration and super resolution with omnidirectional images this paper addresses the reconstruction of high resolution omnidirectional images from multiple low resolution images with inexact registration when omnidirectional images from low resolution vision sensors can be uniquely mapped on the 2 sphere such a reconstruction can be described as a transform domain super resolution problem in a spherical imaging framework we describe how several spherical images with arbitrary rotations in the so 3 rotation group contribute to the reconstruction of a high resolution image with help of the spherical fourier transform sft as low resolution images might not be perfectly registered in practice the impact of inaccurate alignment on the transform coefficients is analyzed we then cast the joint registration and super resolution problem as a total least squares norm minimization problem in the sft domain a l1 regularized total least squares problem is considered and solved efficiently by interior point methods experiments with synthetic and natural images show that the proposed methods lead to effective reconstruction of high resolution images even when large registration errors exist in the low resolution images the quality of the reconstructed images also increases rapidly with the number of low resolution images which demonstrates the benefits of the proposed solution in super resolution schemes finally we highlight the benefit of the additional regularization constraint that clearly leads to reduced noise and improved reconstruction quality

damage spreading and critical exponents for model a ising dynamics using damage spreading and heat bath dynamics we study the ising model in 2 and 3 dimensions with non conservative dynamics our algorithm differs in some important points from previous ones which makes it rather efficient we give estimates for the exponent z which seem to be the most precise published so far 2 172 0 006 for d 2 2 032 0 004 for d 3 we also give precise estimates of the exponent introduced by janssen et al z phys b 73 1989 539 and of analogous but in principle independent exponents we find surprisingly that some of the latter agree with and give an explanation for this

automatic line extraction in uncalibrated omnidirectional cameras with revolution symmetry revolution symmetry is a realistic assumption for modelling the majority of catadioptric and dioptric cameras in central systems it can be described by a projection model based on radially symmetric distortion in these systems straight lines are projected on curves called line images these curves have in general more than two degrees of freedom and their shape strongly depends on the particular camera configuration therefore the existing line extraction methods for this kind of omnidirectional cameras require the camera calibration by contrast with the perspective case where the calibration is not involved in the shape of the projected line image however this drawback can be considered as an advantage because the shape of the line images can be used for self calibration in this paper we present a novel method to extract line images in uncalibrated omnidirectional images which is valid for radially symmetric central systems in this method we propose using the plumb line constraint to find closed form solutions for different types of camera systems dioptric or catadioptric the inputs of the proposed method are points belonging to the line images and their intensity gradient the gradient information allows to reduce the number of points needed in the minimal solution improving the result and the robustness of the estimation the scheme is used in a line image extraction algorithm to obtain lines from uncalibrated omnidirectional images without any assumption about the scene the algorithm is evaluated with synthetic and real images showing good performance the results of this work have been implemented in an open source matlab toolbox for evaluation and research purposes

camera calibration with distortion models and accuracy evaluation a camera model that accounts for major sources of camera distortion namely radial decentering and thin prism distortions is presented the proposed calibration procedure consists of two steps 1 the calibration parameters are estimated using a closed form solution based on a distribution free camera model and 2 the parameters estimated in the first step are improved iteratively through a nonlinear optimization taking into account camera distortions according to minimum variance estimation the objective function to be minimized is the mean square discrepancy between the observed image points and their inferred image projections computed with the estimated calibration parameters the authors introduce a type of measure that can be used to directly evaluate the performance of calibration and compare calibrations among different systems the validity and performance of the calibration procedure are tested with both synthetic data and real images taken by tele and wide angle lenses

scale space analysis and active contours for omnidirectional images a new generation of optical devices that generate images covering a larger part of the field of view than conventional cameras namely catadioptric cameras is slowly emerging these omnidirectional images will most probably deeply impact computer vision in the forthcoming years provided that the necessary algorithmic background stands strong in this paper we propose a general framework that helps define various computer vision primitives we show that geometry which plays a central role in the formation of omnidirectional images must be carefully taken into account while performing such simple tasks as smoothing or edge detection partial differential equations pdes offer a very versatile tool that is well suited to cope with geometrical constraints we derive new energy functionals and pdes for segmenting images obtained from catadioptric cameras and show that they can be implemented robustly using classical finite difference schemes various experimental results illustrate the potential of these new methods on both synthetic and natural images

the dynamic critical exponent of the three dimensional ising model we measure the dynamic exponent of the three dimensional ising model using a damage spreading monte carlo approach as described by macisaac and jan we simulate systems froml 5 tol 60 at the critical temperature tc 4 5115 we report a dynamic exponent z 2 35 0 05 a value much larger than the consensus value of 2 02 whereas if we assume logarithmic corrections we find thatz 2 05 0 05

synchronous parallel kinetic monte carlo for continuum diffusion reaction systems a novel parallel kinetic monte carlo kmc algorithm formulated on the basis of perfect time synchronicity is presented the algorithm is intended as a generalization of the standard n fold kmc method and is trivially implemented in parallel architectures in its present form the algorithm is not rigorous in the sense that boundary conflicts are ignored we demonstrate however that in their absence or if they were correctly accounted for our algorithm solves the same master equation as the serial method we test the validity and parallel performance of the method by solving several pure diffusion problems i e with no particle interactions with known analytical solution we also study diffusion reaction systems with known asymptotic behavior and find that for large systems with interaction radii smaller than the typical diffusion length boundary conflicts are negligible and do not affect the global kinetic evolution which is seen to agree with the expected analytical behavior our method is a controlled approximation in the sense that the error incurred by ignoring boundary conflicts can be quantified intrinsically during the course of a simulation and decreased arbitrarily controlled by modifying a few problem dependent simulation parameters

billion atom synchronous parallel kinetic monte carlo simulations of critical 3d ising systems an extension of the synchronous parallel kinetic monte carlo spkmc algorithm developed by martinez et al j comp phys 227 2008 3804 to discrete lattices is presented the method solves the master equation synchronously by recourse to null events that keep all processors time clocks current in a global sense boundary conflicts are resolved by adopting a chessboard decomposition into non interacting sublattices we find that the bias introduced by the spatial correlations attendant to the sublattice decomposition is within the standard deviation of serial calculations which confirms the statistical validity of our algorithm we have analyzed the parallel efficiency of spkmc and find that it scales consistently with problem size and sublattice partition we apply the method to the calculation of scale dependent critical exponents in billion atom 3d ising systems with very good agreement with state of the art multispin simulations

structure from motion with line segments under relaxed endpoint constraints we present a novel structure from motion pipeline which estimates motion and wiry 3d structure from imaged line segments across multiple views although the position and orientation of line segments can be determined more accurately than point features the instability of their endpoints and the fact that lines are not constrained by epipolar geometry diverted most research focus away to point based methods in our approach we tackle the problem of instable endpoints by utilizing relaxed constraints on their positions both during matching and as well in the following bundle adjustment stage furthermore we gain efficiency in estimating trifocal image relations by decoupling rotation and translation to this end a novel linear solver for relative translation estimation given rotations from five line correspondences in three views is introduced extensive experiments on long image sequences show that our line based structure from motion pipeline advantageously complements point based methods giving more meaningful 3d representation for indoor scenarios

a posteriori evaluation of wave reflection for adaptive analysis of wave propagation in unbounded domains an adaptive analysis procedure is proposed as a new paradigm with enhanced efficiency and reliability for numerical analysis of wave propagation in unbounded domains in the context of one dimensional wave propagation a local solution procedure is designed based on the method of characteristics for a posteriori evaluation of reflected waves it is shown that the strain associated with the reflected wave exhibit excellent correlation with the order of the absorbing boundary condition employed and thus can effectively be used as an error estimator a simple adaptive analysis algorithm is designed to demonstrate the use of the error estimator in adaptively adjusting the order of the absorbing boundary condition to control within predetermined tolerance spurious wave reflection from the boundary of truncation this leads to the use of an optimal order absorbing boundary condition that results in solutions of desired accuracy

hp version discontinuous galerkin methods for hyperbolic conservation laws abstract the development of hp version discontinuous galerkin methods for hyperbolic conservation laws is presented in this work a priori error estimates are derived for a model class of linear hyperbolic conservation laws these estimates are obtained using a new mesh dependent norm that reflects the dependence of the approximate solution on the local element size and the local order of approximation the results generalize and extend previous results on mesh dependent norms to hp version discontinuous galerkin methods a posteriori error estimates which provide bounds on the actual error are also developed in this work numerical experiments verify the a priori estimates and demonstrate the effectiveness of the a posteriori estimates in providing reliable estimates of the actual error in the numerical solution

robust metric calibration of non linear camera lens distortion camera lens distortion is crucial to obtain the best performance cameral model up to now different techniques exist which try to minimize the calibration error using different lens distortion models or computing them in different ways some compute lens distortion camera parameters in the camera calibration process together with the intrinsic and extrinsic ones others isolate the lens distortion calibration without using any template and basing the calibration on the deformation in the image of some features of the objects in the scene like straight lines or circles these lens distortion techniques which do not use any calibration template can be unstable if a complete camera lens distortion model is computed they are named non metric calibration or self calibration methods traditionally a camera has been always best calibrated if metric calibration is done instead of self calibration this paper proposes a metric calibration technique which computes the camera lens distortion isolated from the camera calibration process under stable conditions independently of the computed lens distortion model or the number of parameters to make it easier to resolve this metric technique uses the same calibration template that will be used afterwards for the calibration process therefore the best performance of the camera lens distortion calibration process is achieved which is transferred directly to the camera calibration process

visual attention on the sphere human visual system makes an extensive use of visual attention in order to select the most relevant information and speed up the vision process inspired by visual attention several computer models have been developed and many computer vision applications rely today on such models however the actual algorithms are not suitable to omnidirectional images which contain a significant amount of geometrical distorsion in this paper we present a novel computational approach that performs in spherical geometry and thus is suitable for omnidirectional images following one of the actual models of visual attention the spherical saliency map is obtained by fusing together intensity chromatic and orientation spherical cue conspicuity maps that are themselves obtained through multiscale analysis on the sphere finally the consecutive maxima in the spherical saliency map represent the spots of attention on the sphere in the experimental part the proposed method is then compared to the standard one using a synthetic image also we provide examples of spots detection in real omnidirectional scenes which show its advantages finally an experiment illustrates the homogeneity of the detected visual attention in omnidirectional images

nonmetric calibration of wide angle lenses and polycameras images taken with wide angle cameras tend to have severe distortions which pull points towards the optical center this paper proposes a simple method for recovering the distortion parameters without the use of any calibration objects since distortions cause straight lines in the scene to appear as curves in the image our algorithm seeks to find the distortion parameters that map the image curves to straight lines the user selects a small set of points along the image curves recovery of the distortion parameters is formulated as the minimization of an objective function which is designed to explicitly account for noise in the selected image points experimental results are presented for synthetic data as well as real images we also present the idea of a polycamera which is defined as a tightly packed camera cluster possible configurations are proposed to capture very large fields of view such camera clusters tend to have a nonsingle viewpoint we therefore provide analysis of what we call the minimum working distance for such clusters finally we present results for a polycamera consisting of four wide angle sensors having a minimum working distance of about 4 m on undistorting the acquired images using our proposed technique we create real time high resolution panoramas

true multi image alignment and its application to mosaicing and lens distortion correction multiple images of a scene are related through 2d 3d view transformations and linear and nonlinear camera transformations we present an algorithm for true multi image alignment that does not rely on the measurements of a reference image being distortion free the algorithm is developed to specifically align and mosaic images using parametric transformations in the presence of lens distortion when lens distortion is present none of the images can be assumed to be ideal in our formulation all the images are modeled as intensity measurements represented in their respective coordinate systems each of which is related to an ideal coordinate system through an interior camera transformation and an exterior view transformation the goal of the accompanying algorithm is to compute an image in the ideal coordinate system while solving for the transformations that relate the ideal system with each of the data images key advantages of the technique presented in this paper are i no reliance on one distortion free image ii ability to register images and compute coordinate transformations even when the multiple images are of an extended scene with no overlap between the first and last frame of the sequence and iii ability to handle linear and nonlinear transformations within the same framework results of applying the algorithm are presented for the correction of lens distortion and creation of video mosaics