generalizing the hough transform to detect arbitrary shapes abstract the hough transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve the initial work showed how to detect both analytic curves 1 2 and non analytic curves 3 but these methods were restricted to binary edge images this work was generalized to the detection of some analytic curves in grey level images specifically lines 4 circles 5 and parabolas 6 the line detection case is the best known of these and has been ingeniously exploited in several applications 7 8 9 we show how the boundaries of an arbitrary non analytic shape can be used to construct a mapping between image space and hough transform space such a mapping can be exploited to detect instances of that particular shape in an image furthermore variations in the shape such as rotations scale changes or figure ground reversals correspond to straightforward transformations of this mapping however the most remarkable property is that such mappings can be composed to build mappings for complex shapes from the mappings of simpler component shapes this makes the generalized hough transform a kind of universal transform which can be used to find arbitrarily complex shapes

algorithms for approximate string matching the edit distance between strings a 1 a m and b 1 b n is the minimum cost s of a sequence of editing steps insertions deletions changes that convert one string into the other a well known tabulating method computes s as well as the corresponding editing sequence in time and in space o mn in space o min m n if the editing sequence is not required starting from this method we develop an improved algorithm that works in time and in space o s min m n another improvement with time o s min m n and space o s min s m n is given for the special case where all editing steps have the same cost independently of the characters involved if the editing sequence that gives cost s is not required our algorithms can be implemented in space o min s m n since s o max m n the new methods are always asymptotically as good as the original tabulating method as a by product algorithms are obtained that given a threshold value t test in time o t min m n and in space o min t m n whether s t finally different generalized edit distances are analyzed and conditions are given under which our algorithms can be used in conjunction with extended edit operation sets including for example transposition of adjacent characters

on the implementation of inelastic constitutive equations with special reference to large deformation problems abstract methods for finite element analysis of inelastic problems are reviewed problems with currently popular methods based on rate principles of virtual work are pointed out a formulation is presented based on the exact incremental virtual work equation the procedure for integration of the constitutive rate equations to obtain incremental constitutive equations is based on the assumption of a constant strain rate or straight strain path during the increment full newton raphson iteration is used to solve the resulting set of nonlinear equations the treatment of the constitutive equations in this newton raphson scheme leads to a linearized form which is substantially different from the classical rate equations the procedure is implemented in a finite element program and its effectiveness is shown in a number of examples

analytical cpp in energy mapped stress space application to a modified drucker prager yield surface in conventional stress space the closest point projection cpp of computational plasticity in general does not provide the closest point in a euclidean sense but rather in an energy metric as an alternative this contribution discusses an energy mapped stress space such that cpp is indeed the closest point in a strict euclidean sense this perspective clarifies which yield surfaces can be handled analytically analytical solutions are possible if the cpp can be expressed as a polynomial of order 4 or less this is demonstrated by means of a modified drucker prager yield surface in which the hydrostatic tensile apex is removed through the use of hyperbolic meridians

a semi analytical integration method for j2 flow theory of plasticity with linear isotropic hardening abstract in this paper an exact time integration scheme is presented for von mises elastoplasticity with linear isotropic hardening at small deformations the method is based on the constant strain rate assumption which is widely accepted in displacement based finite element applications the deviatoric form of the rate equation using the method proposed by krieg and krieg in r d krieg d b krieg accuracies of numerical solution methods for the elastic perfectly plastic model j press vess technol trans asme 99 1977 510 515 is rewritten to a system of nonlinear odes with two scalar functions the radius of the mises circle and an angle obtained by using the scalar product of the stress deviator and the strain rate the time integration of these functions gives an exact solution in implicit form using the incomplete beta function in addition by the exact linearization of this new semi analytical solution a stress updating algorithm and the consistent tangent operator are derived the numerical performance and accuracy of the proposed method are illustrated on numerical examples moreover a comparison of the proposed method with the well known radial return method is included

flexible spatial configuration of local image features local image features have been designed to be informative and repeatable under rigid transformations and illumination deformations even though current state of the art local image features present a high degree of repeatability their local appearance alone usually does not bring enough discriminative power to support a reliable matching resulting in a relatively high number of mismatches in the correspondence set formed during the data association procedure as a result geometric filters commonly based on global spatial configuration have been used to reduce this number of mismatches however this approach presents a trade off between the effectiveness to reject mismatches and the robustness to nonrigid deformations in this paper we propose two geometric filters based on a semilocal spatial configuration of local features that are designed to be robust to nonrigid deformations and to rigid transformations without compromising its efficacy to reject mismatches we compare our methods to the hough transform which is an efficient and effective mismatch rejection step based on the global spatial configuration of features in these comparisons our methods are shown to be more effective in the task of rejecting mismatches for rigid transformations and nonrigid deformations at comparable time complexity figures finally we demonstrate how we can integrate these methods in a probabilistic recognition system such that the final verification step uses not only the similarity between features but also their semilocal configuration

monge properties of sequence alignment alignment is an important sequence comparison measure algorithms that compute alignments have a wide range of applications namely in bioinformatic tools alignments can be computed as maximum scoring paths in alignment dags in this paper we study the properties of matrices that contain alignment scores between a string and all the sub strings of another string we focus on the fact that these matrices have the monge property and are sparse in some sense related studies were recently presented for hsm and dist matrices leading to o nlogn procedure for multiplying those matrices where o n bounds the sizes of the strings our results strictly generalize previous solutions we measure the sparseness of the matrices with variable d and present an algorithm for matrix multiplication in o email protected log 3 email protected time which we improve to o email protected log 2 email protected within the same space we discuss applications of this algorithm namely fully incremental alignment and alignment update we study experimentally the performance of the methods we propose

a feature point matching based on spatial order constraints bilateral neighbor vote feature point matching is a fundamental and challenging problem in many computer vision applications in this paper a robust feature point matching algorithm named spatial order constraints bilateral neighbor vote socbv is proposed to remove outliers for a set of matches including outliers between two images a directed k nearest neighbor knn graph of match sets is generated and the problem of feature point matching is formulated as a binary discrimination problem in the discrimination process the class labeled matrix is built via the spatial order constraints defined on the edges that connect a point to its knn then the posterior inlier class probability of each match is estimated with the knn density estimation and spatial order constraints the vote of each match is determined by averaging all posterior class probabilities that originate from its associative inliers set and is used for removing outliers the algorithm iteratively removes outliers from the directed graph and recomputes the votes until the stopping condition is satisfied compared with other popular algorithms such as ransac rsoc gtm soc and wgtm experiments under various testing data sets demonstrate strong robustness for the proposed algorithm

algorithmic issues for three invariant hyperplastic critical state models implicit stress integration and the consistent tangents are presented for critical state hyperplasticity models which include a dependence on the third invariant of stress an elliptical deviatoric yielding criterion 43 is incorporated within the family of geotechnical models first proposed by collins and hilder 8 an alternative expression for the yield function is proposed and the consequences of different forms of that function are revealed in terms of the stability and efficiency of the stress return algorithm errors associated with the integration scheme are presented it is shown how calibration of the two new material constants is achieved through examining one dimesional consolidation tests and undrained triaxial compression data material point simulations of drained triaxial compression tests are then compared with established experimental results strain probe analyses are used to demonstrate the concepts of energy dissipation and stored plastic work along with the robustness of the integration method over twenty finite element boundary value problems are then simulated these include single three dimensional element tests plane strain footing analyses and cavity expansion tests the rapid convergence of the global newton raphson procedure using the consistent tangent is demonstrated in small strain and finite deformation simulations

reuleaux plasticity analytical backward euler stress integration and consistent tangent analytical backward euler stress integration is presented for a deviatoric yielding criterion based on a modified reuleaux triangle the criterion is applied to a cone model which allows control over the shape of the deviatoric section independent of the internal friction angle on the compression meridian the return strategy and consistent tangent are fully defined for all three regions of principal stress space in which elastic trial states may lie errors associated with the integration scheme are reported these are shown to be less than 3 for the case examined run time analysis reveals a 2 5 5 0 times speed up at a material point over the iterative newton raphson backward euler stress return scheme two finite element analyses are presented demonstrating the speed benefits of adopting this new formulation in larger boundary value problems the simple modified reuleaux surface provides an advance over mohr coulomb and drucker prager yield envelopes in that it incorporates dependencies on both the lode angle and intermediate principal stress without incurring the run time penalties of more sophisticated models

design of simple low order finite elements for large strain analysis of nearly incompressible solids a simple four node quadrilateral and an eight node hexahedron for large strain analysis of nearly incompressible solids are proposed based on the concept of deviatoric volumetric split and the replacement of the compatible deformation gradient with an assumed modified counterpart the formulation developed is applicable to arbitrary material models the closed form of the corresponding exact tangent stiffnesses which have a particularly simple structure is derived it ensures asymptotically quadratic rates of convergence of the newton raphson scheme employed in the solution of the implicit finite element equilibrium equations from a practical point of view the incorporation of the proposed elements into existing codes is straightforward it requires only small changes in the routines of the standard displacement based 4 node quadrilateral and 8 node brick a comprehensive set of numerical examples involving hyperelasticity as well as multiplicative elasto plasticity is provided it illustrates the performance of the proposed elements over a wide range of applications including strain localisation problems metal forming simulation and adaptive analysis

incremental string comparison the problem of comparing two sequences a and b to determine their longest common subsequence lcs or the edit distance between them has been much studied in this paper we consider the following incremental version of these problems given an appropriate encoding of a comparison between a and b can one incrementally compute the answer for a and bb and the answer for a and bb with equal efficiency where b is an additional symbol our main result is a theorem exposing a surprising relationship between the dynamic programming solutions for two such adjacent problems given a threshold k on the number of differences to be permitted in an alignment the theorem leads directly to an o k algorithm for incrementally computing a new solution from an old one as contrasts the o k2 time required to compute a solution from scratch we further show with a series of applications that this algorithm is indeed more powerful than its nonincremental counterpart we show this by solving the applications with greater asymptotic efficiency than heretofore possible for example we obtain o nk algorithms for the longest prefix approximate match problem the approximate overlap problem and cyclic string comparison

consistent tangent operators for rate independent elastoplasticity abstract it is shown that for problems involving rate constitutive equations such as rate independent elastoplasticity the notion of consistency between the tangent stiffness operator and the integration algorithm employed in the solution of the incremental problem plays a crucial role in preserving the quadratic rate of asymptotic convergence of iterative solution schemes based upon newton s method within the framework of closest point projection algorithms a methodology is presented whereby tangent operators consistent with this class of algorithms may be systematically developed to wit associative j 2 flow rules with general nonlinear kinematic and isotropic hardening rules as well as a class of non associative flow rules are considered the resulting iterative solution scheme preserves the asymptotic quadratic convergence characteristic of newton s method whereas use of the socalled elastoplastic tangent in conjunction with a radial return integration algorithm a procedure often employed results in newton type of algorithms with suboptimal rate of convergence application is made to a set of numerical examples which include saturation hardening laws of exponential type

scale affine invariant interest point detectors in this paper we propose a novel approach for detecting interest points invariant to scale and affine transformations our scale and affine invariant detectors are based on the following recent results 1 interest points extracted with the harris detector can be adapted to affine transformations and give repeatable results geometrically stable 2 the characteristic scale of a local structure is indicated by a local extremum over scale of normalized derivatives the laplacian 3 the affine shape of a point neighborhood is estimated based on the second moment matrix our scale invariant detector computes a multi scale representation for the harris interest point detector and then selects points at which a local measure the laplacian is maximal over scales this provides a set of distinctive points which are invariant to scale rotation and translation as well as robust to illumination changes and limited changes of viewpoint the characteristic scale determines a scale invariant region for each point we extend the scale invariant detector to affine invariance by estimating the affine shape of a point neighborhood an iterative algorithm modifies location scale and neighborhood of each point and converges to affine invariant points this method can deal with significant affine transformations including large scale changes the characteristic scale and the affine shape of neighborhood determine an affine invariant region for each point we present a comparative evaluation of different detectors and show that our approach provides better results than existing methods the performance of our detector is also confirmed by excellent matching resultss the image is described by a set of scale affine invariant descriptors computed on the regions associated with our points

global propagation of affine invariant features for robust matching local invariant features have been successfully used in image matching to cope with viewpoint change partial occlusion and clutters however when these factors become too strong there will be a lot of mismatches due to the limited repeatability and discriminative power of features in this paper we present an efficient approach to remove the false matches and propagate the correct ones for the affine invariant features which represent the state of the art local invariance first a pair wise affine consistency measure is proposed to evaluate the consensus of the matches of affine invariant regions the measure takes into account both the keypoint location and the region shape size and orientation based on this measure a geometric filter is then presented which can efficiently remove the outliers from the initial matches and is robust to severe clutters and non rigid deformation to increase the correct matches we propose a global match refinement and propagation method that simultaneously finds a optimal group of local affine transforms to relate the features in two images the global method is capable of producing a quasi dense set of matches even for the weakly textured surfaces that suffer strong rigid transformation or non rigid deformation the strong capability of the proposed method in dealing with significant viewpoint change non rigid deformation and low texture objects is demonstrated in experiments of image matching object recognition and image based rendering

hypothesis testing a framework for analyzing and optimizing hough transform performance in this paper a formal quantitative approach to designing optimum hough transform ht algorithms is proposed this approach takes the view that a ht is a hypothesis testing method each sample in the ht array implements a test to determine whether a curve with the given parameters fits the edge point data this view allows the performance of ht algorithms to be quantified the power function which gives the probability of rejection as a function of the underlying parametric distribution of data points is shown to be the fundamentally important characteristic of ht behaviour attempting to make the power function narrow is a formal approach to optimizing ht performance to illustrate how this framework is useful the particular problem of line detection is discussed in detail it is shown that the hypothesis testing framework leads to a redefinition of the ht in which the values are a measure of the distribution of points around a curve rather than the number of points on a curve this change dramatically improves the sensitivity of the method to small structures the solution to many ht design problems can be posed within the framework including optimal quantizations and optimum sampling of the parameter space in this paper the authors consider the design of optimum i d filters which can be used to sharpen the peak structure in parameter space results on several real images illustrate the improvements obtained

a probabilistic relaxation labeling framework for reducing the noise effect in geometric biclustering of gene expression data biclustering is an important method in dna microarray analysis which can be applied when only a subset of genes is co expressed in a subset of conditions unlike standard clustering analyses biclustering methodology can perform simultaneous classification on two dimensions of genes and conditions in a microarray data matrix however the performance of biclustering algorithms is affected by the inherent noise in data types of biclusters and computational complexity in this paper we present a geometric biclustering method based on the hough transform and the relaxation labeling technique unlike many existing biclustering algorithms we first consider the biclustering patterns through geometric interpretation such a perspective makes it possible to unify the formulation of different types of biclusters as hyperplanes in spatial space and facilitates the use of a generic plane finding algorithm for bicluster detection in our algorithm the hough transform is employed for hyperplane detection in sub spaces to reduce the computational complexity then sub biclusters are combined into larger ones under the probabilistic relaxation labeling framework our simulation studies demonstrate the robustness of the algorithm against noise and outliers in addition our method is able to extract biologically meaningful biclusters from real microarray gene expression data

a performance evaluation of local descriptors in this paper we compare the performance of descriptors computed for local interest regions as for example extracted by the harris affine detector mikolajczyk k and schmid c 2004 many different descriptors have been proposed in the literature it is unclear which descriptors are more appropriate and how their performance depends on the interest region detector the descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the detector our evaluation uses as criterion recall with respect to precision and is carried out for different image transformations we compare shape context belongie s et al april 2002 steerable filters freeman w and adelson e setp 1991 pca sift ke y and sukthankar r 2004 differential invariants koenderink j and van doorn a 1987 spin images lazebnik s et al 2003 sift lowe d g 1999 complex filters schaffalitzky f and zisserman a 2002 moment invariants van gool l et al 1996 and cross correlation for different types of interest regions we also propose an extension of the sift descriptor and show that it outperforms the original method furthermore we observe that the ranking of the descriptors is mostly independent of the interest region detector and that the sift based descriptors perform best moments and steerable filters show the best performance among the low dimensional descriptors

non associated reuleaux plasticity analytical stress integration and consistent tangent for finite deformation mechanics analytical backward euler stress integration is presented for a volumetrically non associated pressure sensitive yield criterion based on a modified reuleaux triangle this advances previous work on associated reuleaux plasticity using energy mapped stress space the analytical solution is 2 4 times faster than a standard numerical backward euler algorithm the merit in transforming to and operating in this space is that the stress return is truly the closest point on the surface to the elastic trial state the paper includes a tension cut off formed by a second cone and describes the steps necessary to allow the model s incorporation within a finite deformation framework finite element results show a 59 runtime saving for a modified reuleaux model over a willam warnke cone giving comparable accuracy in a thick walled cylinder expansion problem the consistent tangent provides asymptotically quadratic convergence in the newton raphson scheme under both i small strain infinitesimal deformation and ii large strain finite deformation finite element simulations it is shown that the introduction of non associated flow changes the plastic deformation field and reduces the heave predicted in a plane strain rigid strip footing problem the proposed model offers a significant improvement over the drucker prager and mohr coulomb formulations by better reproducing the material dependence on the lode angle and intermediate principal stress at little extra computational effort

signal matching through scale space given a collection of similar signals that have been deformed with respect to each other the general signal matching problem is to recover the deformation we formulate the problem as the minimization of an energy measure that combines a smoothness term and a similarity term the minimization reduces to a dynamic system governed by a set of coupled first order differential equations the dynamic system finds an optimal solution at a coarse scale and then tracks it continuously to a fine scale among the major themes in recent work on visual signal matching have been the notions of matching as constrained optimization of variational surface reconstruction and of coarse to fine matching our solution captures these in a precise succinct and unified form results are presented for one dimensional signals a motion sequence and a stereo pair

longest common subsequence problem for unoriented and cyclic strings given a finite set of strings x the longest common subsequence problem lcs consists in finding a subsequence common to all strings in x that is of maximal length lcs is a central problem in stringology and finds broad applications in text compression conception of error detecting codes or biological sequence comparison however in numerous contexts words represent cyclic or unoriented sequences of symbols and lcs must be generalized to consider both orientations and or all cyclic shifts of the strings involved this occurs especially in computational biology when genetic material is sequenced from circular dna or rna molecules in this work we define three variants of lcs when the input words are unoriented and or cyclic we show that these problems are np hard and w 1 hard if parameterized in the number of input strings these results still hold even if the three lcs variants are restricted to input languages over a binary alphabet we also settle the parameterized complexity of our problems for most relevant parameters moreover we study the approximability of these problems we discuss the existence of approximation bounds depending on the cardinality of the alphabet on the length of the shortest sequence and on the number of input sequences for this we prove that maximum independent set in r uniform hypergraphs is w 1 hard if parameterized in the cardinality of the sought independent set and at least as hard to approximate as maximum independent set in graphs

stochastic relaxation gibbs distributions and the bayesian restoration of images we make an analogy between images and statistical mechanics systems pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice like physical system the assignment of an energy function in the physical system determines its gibbs distribution because of the gibbs distribution markov random field mrf equivalence this assignment also determines an mrf image model the energy function is a more convenient and natural mechanism for embodying picture attributes than are the local characteristics of the mrf for a range of degradation mechanisms including blurring nonlinear deformations and multiplicative or additive noise the posterior distribution is an mrf with a structure akin to the image model by the analogy the posterior distribution defines another imaginary physical system gradual temperature reduction in the physical system isolates low energy states annealing or what is the same thing the most probable states under the gibbs distribution the analogous operation under the posterior distribution yields the maximum a posteriori map estimate of the image given the degraded observations the result is a highly parallel relaxation algorithm for map estimation we establish convergence properties of the algorithm and we experiment with some simple pictures for which good restorations are obtained at low signal to noise ratios

rapid non linear finite element analysis of continuous and discontinuous galerkin methods in matlab matlab is adept at the development of concise finite element fe routines however it is commonly perceived to be too inefficient for high fidelity analysis this paper aims to challenge this preconception by presenting two optimised fe codes for both continuous galerkin cg and discontinuous galerkin dg methods although this has previously been achieved for linear elastic problems no such optimised matlab script currently exists which includes the effects of material non linearity to incorporate these elasto plastic effects the externally applied load is split into a discrete number of loadsteps equilibrium is determined at each loadstep between the externally applied load and the arising internal forces using the newton raphson method the optimisation of the scripts is primarily achieved using vectorised blocking algorithms which minimise ram to cache overheads and maximise cache reuse the optimised codes yielded maximum speed gains of 25 7 and 10 1 when compared to the corresponding unoptimised scripts for cg and dg respectively it was identified that with increasing refinement of the mesh the solver time begins to dominate the overall simulation time this bottleneck has a greater disadvantage on the dg code predominantly due the asymmetric nature of the global stiffness matrix the implementation of an efficient solver would see further improvement to the overall run times particularly for large problems

longest common extensions in trees the longest common extension lce of two indices in a string is the length of the longest identical substrings starting at these two indices the lce problem asks to preprocess a string into a compact data structure that supports fast lce queries in this paper we generalize the lce problem to trees and suggest a few applications of lce in trees to tries and xml databases given a labeled and rooted tree t of size n the goal is to preprocess t into a compact data structure that support the following lce queries between subpaths and subtrees in t let v 1 v 2 w 1 and w 2 be nodes of t such that w 1 and w 2 are descendants of v 1 and v 2 respectively lce pp v 1 w 1 v 2 w 2 path path lce return the longest common prefix of the paths v 1 w 1 and v 2 w 2 lce pt v 1 w 1 v 2 path tree lce return maximal path path lce of the path v 1 w 1 and any path from v 2 to a descendant leaf lce tt v 1 v 2 tree tree lce return a maximal path path lce of any pair of paths from v 1 and v 2 to descendant leaves we present the first non trivial bounds for supporting these queries for lce pp queries we present a linear space solution with o log n query time for lce pt queries we present a linear space solution with o log log n 2 query time and complement this with a lower bound showing that any path tree lce structure of size o n polylog n must necessarily use log log n time to answer queries for lce tt queries we present a time space trade off that given any parameter 1 n leads to an o n space and o n query time solution all of these bounds hold on a standard unit cost ram model with logarithmic word size this is complemented with a reduction from the set intersection problem implying that a fast linear space solution is not likely to exist

all highest scoring paths in weighted grid graphs and their application to finding all approximate repeats in strings weighted paths in directed grid graphs of dimension m x n can be used to model the string edit problem which consists of obtaining optimal weighted alignments between substrings of a a m and substrings of b b n we build a data structure in o mn log m time that supports o log m time queries about the weight of any of the o m2n best paths from the vertices in column 0 of the graph to all other vertices using these techniques we present a simple o n2 log n time and theta n 2 space algorithm to find all the locally optimal approximate tandem or nontandem repeats xy within a string of size n this improves by a factor of log n upon several previous algorithms for this problem and is the first algorithm to find all locally optimal repeats for edit graphs with weights in 0 1 1 a slight modification of our techniques yields an o n2 algorithm for the cyclic string comparison problem as compared to o n2 log n for the case of general weights

a comparison of affine region detectors the paper gives a snapshot of the state of the art in affine covariant region detectors and compares their performance on a set of test images under varying imaging conditions six types of detectors are included detectors based on affine normalization around harris mikolajczyk and schmid 2002 schaffalitzky and zisserman 2002 and hessian points mikolajczyk and schmid 2002 a detector of maximally stable extremal regions proposed by matas et al 2002 an edge based region detector tuytelaars and van gool 1999 and a detector based on intensity extrema tuytelaars and van gool 2000 and a detector of salient regions proposed by kadir zisserman and brady 2004 the performance is measured against changes in viewpoint scale illumination defocus and image compression the objective of this paper is also to establish a reference test set of images and performance software so that future detectors can be evaluated in the same framework

accuracy and stability of integration algorithms for elastoplastic constitutive relations an analysis of accuracy and stability of algorithms for the integration of elastoplastic constitutive relations is carried out in this paper reference is made to a very general internal variable formulation of plasticity and to two families of algorithms that generalize the well known trapezoidal and midpoint rules to fit the present context other integration schemes such as the radial return mean normal and closest point procedures are particular cases of this general formulation the meaning of first and second order accuracy in the presence of the plastic consistency condition is examined in detail and the criteria derived are used to identify two second order accurate members of the proposed algorithms a general methodology is also derived whereby the numerical stability properties of integration schemes can be systematically assessed with the aid of this methodology the generalized midpoint rule is seen to have far better stability properties than the generalized trapezoidal rule finally numerical examples are presented that illustrate the performance of the algorithms

improved explicit integration in plasticity the article presents a simple but efficient numerical scheme for the integration of non linear constitutive equations in which the principal reason for the inaccuracy of the classical explicit schemes for example forward euler scheme is effectively eliminated in the newly developed explicit scheme where there is no need for iteration the implementation simplicity of the forward euler scheme and accuracy of the approach which is using the backward euler scheme to integrate the constitutive equations are successfully combined computational performance of the proposed next increment corrects error nice integration scheme particularly regarding the accuracy and the cpu time consumption is first analysed on a case of complex loading of a material point when comparing it to the forward euler backward euler trapezoidal and midpoint integration schemes it turns out that because of its capability of a fast and relatively accurate integration of the constitutive equations the nice scheme is very convenient for the integration of constitutive models where a direct solution technique is used to solve a boundary value problem although the deduction of the new integration scheme is general its implementation for shell applications needs particular care namely in order to satisfy the zero normal stress condition during the whole integration a through thickness strain increment has to be adequately chosen in each integration step the nice scheme which was also implemented into abaqus explicit via user material subroutine vumat interface platform has been additionally compared with the abaqus explicit default integration scheme backward euler and forward euler scheme two loading case studies namely the bending of a square plate and the stretching of a specimen including the onset of necking are considered with two constitutive models the von mises and gtn material model being adopted generally the nice scheme has demonstrated to be advantageous in cases where reasonable accuracy and very fast integration of the constitutive model is demanded which is mostly the case in engineering computations with a direct solution method for example explicit dynamics and metal forming process simulations copyright 2009 john wiley sons ltd

an implicit boundary finite element method with extension to frictional sliding boundary conditions and elasto plastic analyses abstract implicit boundary methods which enrich the interpolation structure with implicit weight functions are straightforward methods for the enforcement of dirichlet boundary conditions in this article we follow the implicit boundary method that uses approximate step functions the step boundary method developed by kumar et al and provide modifications that have several advantages roller boundary conditions have wide practical applications in engineering however the step boundary method for roller boundary conditions with inclinations has yet to be fully formulated through to the final linear system of equations thus we provide a complete derivation that leads to simplified stiffness matrices compared to the original approach which can be implemented directly in fictitious domain finite element analysis the approach is then extended we believe for the first time to the nonlinear cases of frictional boundary conditions and elasto plastic material behaviour the proposed formulation and procedures are validated on a number of example problems that test different aspects of the method

matching widely separated views based on affine invariant regions invariant regions are self adaptive image patches that automatically deform with changing viewpoint as to keep on covering identical physical parts of a scene such regions can be extracted directly from a single image they are then described by a set of invariant features which makes it relatively easy to match them between views even under wide baseline conditions in this contribution two methods to extract invariant regions are presented the first one starts from corners and uses the nearby edges while the second one is purely intensity based as a matter of fact the goal is to build an opportunistic system that exploits several types of invariant regions as it sees fit this yields more correspondences and a system that can deal with a wider range of images to increase the robustness of the system two semi local constraints on combinations of region correspondences are derived one geometric the other photometric they allow to test the consistency of correspondences and hence to reject falsely matched regions experiments on images of real world scenes taken from substantially different viewpoints demonstrate the feasibility of the approach

on the foundations of relaxation labeling processes a large class of problems can be formulated in terms of the assignment of labels to objects frequently processes are needed which reduce ambiguity and noise and select the best label among several possible choices relaxation labeling processes are just such a class of algorithms they are based on the parallel use of local constraints between labels this paper develops a theory to characterize the goal of relaxation labeling the theory is founded on a definition of con sistency in labelings extending the notion of constraint satisfaction in certain restricted circumstances an explicit functional exists that can be maximized to guide the search for consistent labelings this functional is used to derive a new relaxation labeling operator when the restrictions are not satisfied the theory relies on variational cal culus it is shown that the problem of finding consistent labelings is equivalent to solving a variational inequality a procedure nearly identical to the relaxation operator derived under restricted circum stances serves in the more general setting further a local convergence result is established for this operator the standard relaxation labeling formulas are shown to approximate our new operator which leads us to conjecture that successful applications of the standard methods are explainable by the theory developed here observations about con vergence and generalizations to higher order compatibility relations are described

on the statistical analysis of dirty pictures may 7th 1986 professor a f m smith in the chair summary a continuous two dimensional region is partitioned into a fine rectangular array of sites or pixels each pixel having a particular colour belonging to a prescribed finite set the true colouring of the region is unknown but associated with each pixel there is a possibly multivariate record which conveys imperfect information about its colour according to a known statistical model the aim is to reconstruct the true scene with the additional knowledge that pixels close together tend to have the same or similar colours in this paper it is assumed that the local characteristics of the true scene can be represented by a nondegenerate markov random field such information can be combined with the records by bayes theorem and the true scene can be estimated according to standard criteria however the computational burden is enormous and the reconstruction may reflect undesirable largescale properties of the random field thus a simple iterative method of reconstruction is proposed which does not depend on these large scale characteristics the method is illustrated by computer simulations in which the original scene is not directly related to the assumed random field some complications including parameter estimation are discussed potential applications are mentioned briefly

efficient return algorithms for associated plasticity with multiple yield planes a new return method for implicit integration of linear isotropic yield criteria is presented the basic idea is to perform all the manipulations in the principal stress space and thereby achieve very simple formulae for calculating the plastic corrector stresses based on the constant gradient of such criteria the return formulae are in closed form and no iteration is required the method accounts for three types of stress return return to a single yield plane to a discontinuity line at the intersection of two yield planes and to a discontinuity point at the intersection between three or more yield planes the infinitesimal and the consistent elastoplastic constitutive matrix are calculated for each type of stress return as are the conditions to ascertain which type of return is required the method is exemplified with the mohr coulomb yield criterion

nurbs plasticity yield surface representation and implicit stress integration for isotropic inelasticity in numerical analysis the failure of engineering materials is controlled through specifying yield envelopes or surfaces that bound the allowable stress in the material however each surface is distinct and requires a specific equation describing the shape of the surface to be formulated in each case these equations impact on the numerical implementation specifically relating to stress integration of the models and therefore a separate algorithm must be constructed for each model this paper presents for the first time a way to construct yield surfaces using techniques from non uniform rational basis spline nurbs surfaces such that any isotropic convex yield envelope can be represented within the same framework these surfaces are combined with an implicit backward euler type stress integration algorithm to provide a flexible numerical framework for computational plasticity the algorithm is inherently stable as the iterative process starts and remains on the yield surface throughout the stress integration the performance of the algorithm is explored using both material point investigations and boundary value analyses demonstrating that the framework can be applied to a variety of plasticity models

two dimensional object recognition through two stage string matching a two stage string matching method for the recognition of two dimensional 2 d objects is proposed in this work the first stage is a global cyclic string matching the second stage is a local matching with local dissimilarity measure computing the dissimilarity measure function of the input shape and the reference shape are obtained by combining the global matching cost and the local dissimilarity measure the proposed method has the advantage that there is no need to set any parameter in the recognition process experimental results indicate that the hostage string matching approach significantly improves the recognition rates compared to the one stage string matching method

probabilistic relaxation and the hough transform abstract we discuss the recent developments in probabilistic relaxation which is used as a tool for contextual sensory data interpretation the relationship of this technique with the hough transform is then established focusing on the generalised hough transform ght we show that the label probability updating formula of the probabilistic relaxation process exploiting binary relations between object primitives under the assumption that the primitives convey weak context exhibits very close similarity to the voting function employed by a computationally efficient ght we argue that the relationship could be exploited by importing the positive features of the respective techniques to benefit one another specific suggestions for enhancing the respective techniques are mentioned they include the adoption of the representational efficiency of the hough transform to reduce the computational complexity of probabilistic relaxation vice versa in the case of the generalised hough transform it is pointed out that the effect of an unknown object transformation could be dealt with by means of a parallel cooperative interpretation rather than by means of an exhaustive search through the parameter space of a transformation group this has implications in terms of both the storage and computational requirements of the ght it also opens the possibility of using the ght for detecting objects subject to more complex transformations such as affine or perspective the relationship also suggests the possibility of using alternative voting functions which may speed up the object detection process

robust weighted graph transformation matching for rigid and nonrigid image registration this paper presents an automatic point matching algorithm for establishing accurate match correspondences in two or more images the proposed algorithm utilizes a group of feature points to explore their geometrical relationship in a graph arrangement the algorithm starts with a set of matches including outliers between the two images a set of nondirectional graphs is then generated for each feature and its k nearest matches chosen from the initial set using the angular distances between edges that connect a feature point to its k nearest neighbors in the graph the algorithm finds a graph in the second image that is similar to the first graph in the case of a graph including outliers the algorithm removes such outliers one by one according to their strength from the graph and re evaluates the angles until the two graphs are matched or discarded this is a simple intuitive and robust algorithm that is inspired by a previous work experimental results demonstrate the superior performance of this algorithm under various conditions such as rigid and nonrigid transformations ambiguity due to partial occlusions or match correspondence multiplicity scale and larger view variation

a quasi dense approach to surface reconstruction from uncalibrated images this paper proposes a quasi dense approach to 3d surface model acquisition from uncalibrated images first correspondence information and geometry are computed based on new quasi dense point features that are resampled subpixel points from a disparity map the quasi dense approach gives more robust and accurate geometry estimations than the standard sparse approach the robustness is measured as the success rate of full automatic geometry estimation with all involved parameters fixed the accuracy is measured by a fast gauge free uncertainty estimation algorithm the quasi dense approach also works for more largely separated images than the sparse approach therefore it requires fewer images for modeling more importantly the quasi dense approach delivers a high density of reconstructed 3d points on which a surface representation can be reconstructed this fills the gap of insufficiency of the sparse approach for surface reconstruction essential for modeling and visualization applications second surface reconstruction methods from the given quasi dense geometry are also developed the algorithm optimizes new unified functionals integrating both 3d quasi dense points and 2d image information including silhouettes combining both 3d data and 2d images is more robust than the existing methods using only 2d information or only 3d data an efficient bounded regularization method is proposed to implement the surface evolution by level set methods its properties are discussed and proven for some cases as a whole a complete automatic and practical system of 3d modeling from raw images captured by hand held cameras to surface representation is proposed extensive experiments demonstrate the superior performance of the quasi dense approach with respect to the standard sparse approach in robustness accuracy and applicability

efficient all path score computations on grid graphs we study the integer weighted grid all paths scores igaps problem which is given a grid graph to compute the maximum weights of paths between every pair of a vertex on the first row of the graph and a vertex on the last row of the graph we also consider a variant of this problem periodic igaps where the input grid graph is periodic and infinite for these problems we consider both the general dense and the sparse cases for the sparse periodic igaps problem with 0 1 weights we give an o rlog 3 n 2 r time algorithm where r is the number of diagonal edges of weight 1 our result improves upon the previous o nr result by krusche and tiskin for this problem for the periodic igaps problem we give an o cn 2 time algorithm where c is the maximum weight of an edge this improves upon the previous o c 2n 2 algorithm of tiskin we also show a reduction from periodic igaps to igaps this reduction yields o n 2 algorithms for this problem

approximate periods of strings the study of approximately periodic strings is relevant to diverse applications such as molecular biology data compression and computer assisted music analysis here we study different forms of approximate periodicity under a variety of distance functions we consider three related problems for two of which we derive polynomial time algorithms we then show that the third problem is np complete

edge labeling using dictionary based relaxation an improved application of probabilistic relaxation to edge labeling is presented the improvement derives from the use of a representation of the edge process that is internally consistent and which utilizes a more complex description of edge structure the application uses a dictionary to represent permitted labelings of the entire context conveying neighborhood of each pixel details are given of the dictionary approach and the related representation of the edge process a comparison with other edge postprocessing strategies is provided

an improved algorithm for approximate string matching given a text string a pattern string and an integer k a new algorithm for finding all occurrences of the pattern string in the text string with at most k differences is presented both its theoretical and practical variants improve upon the known algorithms

the development and comparison of robust methodsfor estimating the fundamental matrix this paper has two goals the first is to develop a variety of robust methods for the computation of the fundamental matrix the calibration free representation of camera motion the methods are drawn from the principal categories of robust estimators viz case deletion diagnostics m estimators and random sampling and the paper develops the theory required to apply them to non linear orthogonal regression problems although a considerable amount of interest has focussed on the application of robust estimation in computer vision the relative merits of the many individual methods are unknown leaving the potential practitioner to guess at their value the second goal is therefore to compare and judge the methods comparative tests are carried out using correspondences generated both synthetically in a statistically controlled fashion and from feature matching in real imagery in contrast with previously reported methods the goodness of fit to the synthetic observations is judged not in terms of the fit to the observations per se but in terms of fit to the ground truth a variety of error measures are examined the experiments allow a statistically satisfying and quasi optimal method to be synthesized which is shown to be stable with up to 50 percent outlier contamination and may still be used if there are more than 50 percent outliers performance bounds are established for the method and a variety of robust methods to estimate the standard deviation of the error and covariance matrix of the parameters are examined the results of the comparison have broad applicability to vision algorithms where the input data are corrupted not only by noise but also by gross outliers

fast algorithms for finding nearest common ancestors we consider the following problem given a collection of rooted trees answer on line queries of the form what is the nearest common ancester of vertices x and y we show that any pointer machine that solves this problem requires omega log log n time per query in the worst case where n is the total number of vertices in the trees on the other hand we present an algorithm for a random access machine with uniform cost measure and a bound of omega log n on the number of bits per word that requires o 1 time per query and o n preprocessing time assuming that the collection of trees is static for a version of the problem in which the trees can change between queries we obtain an almost linear time and linear space algorithm

robust point matching for nonrigid shapes by preserving local neighborhood structures in previous work on point matching a set of points is often treated as an instance of a joint distribution to exploit global relationships in the point set for nonrigid shapes however the local relationship among neighboring points is stronger and more stable than the global one in this paper we introduce the notion of a neighborhood structure for the general point matching problem we formulate point matching as an optimization problem to preserve local neighborhood structures during matching our approach has a simple graph matching interpretation where each point is a node in the graph and two nodes are connected by an edge if they are neighbors the optimal match between two graphs is the one that maximizes the number of matched edges existing techniques are leveraged to search for an optimal solution with the shape context distance used to initialize the graph matching followed by relaxation labeling updates for refinement extensive experiments show the robustness of our approach under deformation noise in point locations outliers occlusion and rotation it outperforms the shape context and tps rpm algorithms on most scenarios

structural matching in computer vision using probabilistic relaxation in this paper we develop the theory of probabilistic relaxation for matching features extracted from 2d images derive as limiting cases the various heuristic formulae used by researchers in matching problems and state the conditions under which they apply we successfully apply our theory to the problem of matching and recognizing aerial road network images based on road network models and to the problem of edge matching in a stereo pair for this purpose each line network is represented by an attributed relational graph where each node is a straight line segment characterized by certain attributes and related with every other node via a set of binary relations

nurbs plasticity yield surface evolution and implicit stress integration for isotropic hardening this paper extends the non uniform rational basis spline nurbs plasticity framework of coombs et al 2016 to include isotropic hardening of the yield surfaces the approach allows any smooth isotropic yield envelope to be represented by a nurbs surface the key extension provided by this paper is that the yield surface can expand or contract through the movement of control points linked to the level of inelastic straining experienced by the material the model is integrated using a fully implicit backward euler algorithm that constrains the return path to the yield surface and allows the derivation of the algorithmic consistent tangent to ensure optimum convergence of the global equilibrium equations this provides a powerful framework for elasto plastic constitutive models where unlike the majority of models presented in the literature the underlying numerical algorithm and implemented code remains unchanged for different yield surfaces the performance of the algorithm is demonstrated and validated using both material point and boundary values simulations including plane stress plane strain and three dimensional examples for different yield criteria

improving consistency and reducing ambiguity in stochastic labeling an optimization approach we approach the problem of labeling a set of objects from a quantitative standpoint we define a world model in terms of transition probabilities and propose a definition of a class of global criteria that combine both ambiguity and consistency a projected gradient algorithm is developed to minimize the criterion we show that the minimization procedure can be implemented in a highly parallel manner results are shown on several examples and comparisons are made with relaxation labeling techniques

parallel and deterministic algorithms from mrfs surface reconstruction deterministic approximations to markov random field mrf models are derived one of the models is shown to give in a natural way the graduated nonconvexity gnc algorithm proposed by a blake and a zisserman 1987 this model can be applied to smooth a field preserving its discontinuities a class of more complex models is then proposed in order to deal with a variety of vision problems all the theoretical results are obtained in the framework of statistical mechanics and mean field techniques a parallel iterative algorithm to solve the deterministic equations of the two models is presented together with some experiments on synthetic and real images

speeding up the detection of tandem repeats over the edit distance a tandem repeat in a string is a sequence of two or more contiguous approximate copies of a pattern finding an efficient deterministic algorithm to perform an exhaustive search for tandem repeats in a string is an important and practical problem due to the relevance of tandem repeats in several areas including human identity testing disease diagnosis sequence homology and population studies in this paper we present an o nklog 2k occ algorithm to find all approximate tandem repeats within a sequence of length n allowing at most k insertions deletions and mismatches in each repeat our algorithm utilizes the lempel ziv factorization which was previously used in algorithms that locate exact tandem repeats and algorithms that locate tandem repeats with only mismatches the lz framework is combined with speedups for calculating the edit distance achieving a new and efficient exhaustive search for finding tandem repeats in a string

local grayvalue invariants for image retrieval this paper addresses the problem of retrieving images from large image databases the method is based on local grayvalue invariants which are computed at automatically detected interest points a voting algorithm and semilocal constraints make retrieval possible indexing allows for efficient retrieval from a database of more than 1 000 images experimental results show correct retrieval in the case of partial visibility similarity transformations extraneous features and small perspective deformations

approximate string matching using a bidirectional index we study strategies of approximate pattern matching that exploit bidirectional text indexes extending and generalizing ideas of 9 we introduce a formalism called search schemes to specify search strategies of this type then develop a probabilistic measure for the efficiency of a search scheme prove several combinatorial results on efficient search schemes and finally provide experimental computations supporting the superiority of our strategies

lucas kanade 20 years on a unifying framework since the lucas kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision applications range from optical flow and tracking to layered motion mosaic construction and face coding numerous algorithms have been proposed and a wide variety of extensions have been made to the original formulation we present an overview of image alignment describing most of the algorithms and their extensions in a consistent framework we concentrate on the inverse compositional algorithm an efficient algorithm that we recently proposed we examine which of the extensions to lucas kanade can be used with the inverse compositional algorithm without any significant loss of efficiency and which cannot in this paper part 1 in a series of papers we cover the quantity approximated the warp update rule and the gradient descent approximation in future papers we will cover the choice of the error function how to allow linear appearance variation and how to impose priors on the parameters

a class of mixed assumed strain methods and the method of incompatible modes a three field mixed formulation in terms of displacements stresses and an enhanced strain field is presented which encompasses as a particular case the classical method of incompatible modes within this frame work incompatible elements arise as particular compatible mixed approximations of the enhanced strain field the conditions that the stress interpolation contain piece wise constant functions and be l2 ortho gonal to the enhanced strain interpolation ensure satisfaction of the patch test and allow the elimination of the stress field from the formulation the preceding conditions are formulated in a form particularly convenient for element design as an illustration of the methodology three new elements are developed and shown to exhibit good performance a plane 3d elastic plastic quad an axisymmetric element and a thick plate bending quad the formulation described herein is suitable for non linear analysis

approximating edit distance within constant factor in truly sub quadratic time edit distance is a measure of similarity of two strings based on the minimum number of character insertions deletions and substitutions required to transform one string into the other the edit d