eigenfaces vs fisherfaces recognition using class specific linear projection we develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression taking a pattern classification approach we consider each pixel in an image as a coordinate in a high dimensional space we take advantage of the observation that the images of a particular face under varying illumination but fixed pose lie in a 3d linear subspace of the high dimensional image space if the face is a lambertian surface without shadowing however since faces are not truly lambertian surfaces and do indeed produce self shadowing images will deviate from this linear subspace rather than explicitly modeling this deviation we linearly project the image into a subspace in a manner which discounts those regions of the face with large deviation our projection method is based on fisher s linear discriminant and produces well separated classes in a low dimensional subspace even under severe variation in lighting and facial expressions the eigenface technique another method based on linearly projecting the image space to a low dimensional subspace has similar computational requirements yet extensive experimental results demonstrate that the proposed fisherface method has error rates that are lower than those of the eigenface technique for tests on the harvard and yale face databases

a space time finite element method for the wave equation a numerical method is introduced which uses finite elements in time and space simultaneously to solve the wave equation an error analysis for this scheme is presented and the results of several computations this scheme is accurate for time slabs of arbitrary thickness without introducing extra least squares or stabilization terms

comparing images using the hausdorff distance the hausdorff distance measures the extent to which each point of a model set lies near some point of an image set and vice versa thus this distance can be used to determine the degree of resemblance between two objects that are superimposed on one another efficient algorithms for computing the hausdorff distance between all possible relative positions of a binary image and a model are presented the focus is primarily on the case in which the model is only allowed to translate with respect to the image the techniques are extended to rigid motion the hausdorff distance computation differs from many other shape comparison methods in that no correspondence between the model and the image is derived the method is quite tolerant of small position errors such as those that occur with edge detectors and other feature extraction methods it is shown that the method extends naturally to the problem of comparing a portion of a model against an image

shape similarity matching for query by example this paper describes a unified approach for two dimensional 2 d shape matching and similarity ranking of objects by means of a modal representation in particular we propose a new shape similarity metric in the eigenshape space for object image retrieval from a visual database via query by example this differs from prior work which performed point correspondence determination and similarity ranking of shapes in separate steps the proposed method employs selected boundary and or contour points of an object as a coarse to fine shape representation and does not require extraction of connected boundaries or silhouettes it is rotation translation and scale invariant and can handle mild deformations of objects e g due to partial occlusions or pose variations results comparing the unified method with an earlier two step approach using b spline based modal matching and hausdorff distance ranking are presented on retail and museum catalog style still image databases

a unified set of single step algorithms part 2 theory part 1 of this paper1 presents a very general single step algorithm sspj for the numerical integration of first and second order time dependent differential equations in part 2 we present and discuss results of the accuracy and stability analysis for ss11 ss21 ss31 ss22 and ss32 there is also a detailed comparison of ss22 and the newmark algorithm

robust hausdorff distance matching algorithms using pyramidal structures abstract this paper proposes two hausdorff distance hd matching algorithms in which robust hd measures are implemented in pyramidal structures by computer simulations the matching performance of the conventional hd measures and the proposed robust hd matching algorithms using pyramidal structures is compared with real images which are degraded by noise and occlusions

finite elements in space and time for the analysis of generalised visco elastic materials numerical analysis of linear visco elastic materials requires robust and stable methods to integrate partial differential equations in both space and time in this paper symmetric space time finite element operators are derived for the first time for elementary linear elastic spring and linear viscous dashpot these can thereafter be assembled in parallel and in series to simulate an arbitrarily complex linear visco elastic behaviour the flexibility of the proposed method allows the formulation of the behaviour which closely reflects physical processes an efficient algorithm is proposed to use the generated elementary matrices in a way that is comparable with finite difference schemes in terms of both processor and memory costs this unconditionally stable and convergent procedure is equally valid for space domains in which geometry or material properties evolve with time copyright c 2013 john wiley sons ltd

spatially eigen weighted hausdorff distances for human face recognition abstract hausdorff distance is an efficient measure of the similarity of two point sets in this paper we propose a new spatially weighted hausdorff distance measure for human face recognition the weighting function used in the hausdorff distance measure is based on an eigenface which has a large value at locations of importance facial features and can reflect the face structure more effectively two modified hausdorff distances namely spatially eigen weighted hausdorff distance sewhd and spatially eigen weighted doubly hausdorff distance sew2hd are proposed which incorporate the information about the location of important facial features such as eyes mouth and face contour so that distances at those regions will be emphasized experimental results based on a combination of the orl mit and yale face databases show that sew2hd can achieve recognition rates of 83 90 and 92 for the first one the first three and the first five likely matched faces respectively while the corresponding recognition rates of sewhd are 80 83 and 88 respectively

algorithmically imposed thermodynamic compliance for material models in mechanical simulations using the aim method thermodynamic irreversibility can be imposed on empirical material behaviour by using an appropriate algorithm which takes the path dependence of the degradation process into account this new algorithm algorithmically imposed mechanics aim for algorithmically irreversible mechanics is described and the convergence and unicity of the solutions obtained are proven aim is applicable to a range of mechanical behaviour and is demonstrated to work in conjunction with non local damage with rotating cracks as well as a mixed plastic and damage behaviour copyright c 2015 john wiley sons ltd

numerical null controllability of the 1d linear schrodinger equation abstract this paper deals with the numerical approximation to boundary controls that drive the solution to the 1 d linear schrodinger equation to a prescribed state at a final time using ideas from fursikov and imanuvilov we consider the control that minimizes over the class of admissible controls a functional that involves weighted integrals with weights that blow up at t we will see that this extremal problem is equivalent to a differential problem that is fourth order in space and second order in time adapting some numerical techniques applied by the first author and munch to the heat equation we approximate the variational formulation by introducing appropriate space time finite elements that are c 1 in space and c 0 in time we present two approaches the second one relies on a change of variable which leads to a lower condition number for the stiffness matrix the results of some experiments show the efficiency of these methods

a three dimensional finite element formulation for thermoviscoelastic orthotropic media summary this paper is concerned with the development of a numerical algorithm for the solution of the uncoupled quasistatic initial boundary value problem involving orthotropic linear viscoelastic media undergoing thermal and or mechanical deformation the constitutive equations expressed in integral form involving the relaxation moduli are transformed into an incremental algebraic form prior to development of the nite element formulation this incrementalization is accomplished in closed form and results in a recursive relationship which leads to the need of solving a simple set of linear algebraic equations only for the extraction of the nite element solution use is made of a dirichlet prony series representation of the relaxation moduli in order to derive the recursive relationship and thereby eliminate the storage problem that arises when dealing with materials possessing memory three illustrative example problems are included to demonstrate the method 1997 by john wiley sons ltd

line based recognition using a multidimensional hausdorff distance a line feature based approach for model based recognition using a four dimensional hausdorff distance is proposed this approach reduces the problem of finding the rotation scaling and translation transformations between a model and an image to the problem of finding a single translation minimizing the hausdorff distance between two sets of points in a four dimensional space the implementation of the proposed algorithm can be naturally extended to higher dimensional spaces to efficiently find correspondences between n dimensional patterns the method performance and sensitivity to segmentation problems are quantitatively characterized using an experimental protocol with simulated data it is shown that the algorithm performs well is robust to occlusion and outliers and that it degrades nicely as the segmentation problems increase experiments with real images are also presented

a unified set of single step algorithms part 1 general formulation and applications a general algorithm for a single step time marching scheme for use in dynamic or diffusion equations is presented this algorithm is easily programmed in its universal form for all orders of approximation and covers most of the currently used schemes as well as presenting many new possibilities in many cases it presents a computationally advantageous form over conventional procedures this is particularly so when compared with the newmark algorighm and its variants

solution of linear elastodynamics problems with space time finite elements on structured and unstructured meshes abstract a new implicit approach for the solution of linear elastodynamics problems on structured and unstructured meshes with space time finite elements is suggested new weak formulations are based on time continuous tcg and discontinuous tdg galerkin methods it was shown that for structured meshes the new tcg method has a higher order of accuracy by a factor of two than that of the standard tcg method at the same number of degrees of freedom the accuracy of the new tcg method is one order higher than the accuracy of the standard tdg method the introduction of new weighting functions for the weak formulations of the tcg and tdg methods allows control of the high frequency behavior without degradation of accuracy of the methods a variable number of elements in the time direction as well as a variable order of polynomial time approximations of finite elements for time slabs allows the implementation of a coupled space time adaptive procedure using structured or unstructured meshes numerical examples for 1 d problems demonstrate the effectiveness of the technique

continuous and discontinuous galerkin methods with finite elements in space and time for parallel computing of viscoelastic deformation abstract new non symmetric variational and discretized formulations with space time finite elements are proposed for viscoelastic problems based on the continuous galerkin method cgm and discontinuous galerkin method dgm viscoelastic behaviour is described by the three parameter malvern model which is represented by means of internal variables it allows to use only differential equations for the constitutive equations instead of integrodifferential ones the variational formulation reduces to two types of equations for total displacements and internal displacements internal variables namely to the equilibrium equation and the evolution equation for the internal displacements which are fulfilled in the weak form using continuous trial functions a continuous space time finite element formulation is obtained with simultaneous discretization in space and time subdividing the total observation time interval into time slabs and introducing discontinuous trial functions being continuous within time slabs and allowing jumps across interfaces a more general discontinuous finite element formulation is obtained the difference between these two formulations for one time slab consists in the satisfaction of initial conditions which are fulfilled exactly for the continuous formulation and in a weak form for the discontinuous case the proposed approach has some very attractive advantages with respect to semidiscretization methods regarding the possibility of adaptive space time refinements and parallel processing on mimd parallel computers the considered numerical examples show the effectiveness of simultaneous space time finite element calculations and a high convergence rate for adaptive refinement numerical efficiency is an advantage of dgm in comparison with cgm for discontinuously changing e g piecewise constant boundary conditions in time

line segment hausdorff distance on face matching abstract a novel concept of line segment hausdorff distance is proposed in this paper researchers apply hausdorff distance to measure the similarity of two point sets it is extended here to match two sets of line segments the new approach has the advantage to incorporate structural and spatial information to compute the similarity the added information can conceptually provide more and better distinctive capability for recognition this would strengthen and enhance the matching process of similar objects such as faces the proposed technique has been applied online segments generated from the edge maps of faces with encouraging result that supports the concept experimentally the results also implicate that line segments could provide sufficient information for face recognition this might imply a new way for face coding and recognition

comparing face images using the modified hausdorff distance abstract we introduce a novel methodology applicable to face matching and fast screening of large facial databases the proposed shape comparison method operates on edge maps and derives holistic similarity measures yet it does not require solving the point correspondence problem while the use of edge images is important to introduce robustness to changes in illumination the lack of point to point matching delivers speed and tolerance to local non rigid distortions in particular we propose a face similarity measure derived as a variant of the hausdorff distance by introducing the notion of a neighborhood function n and associated penalties p experimental results on a large set of face images demonstrate that our approach produces excellent recognition results even when less than 3 of the original grey scale face image information is stored in the face database gallery these results implicate that the process of face recognition may start at a much earlier stage of visual processing than it was earlier suggested we argue that edge like retinal images of faces are initially screened at a glance without the involvement of high level cognitive functions thus delivering high speed and reducing computational complexity

gauge choice in witten s energy expression witten s equation not d psi 0 can be interpreted as a gauge fixing condition for classical supergravity we rigorously prove the existence of asymptotically constant solutions of the more general gauge condition not d psi a psi for almost all endomorphismsa of the spin bundle each gives an expression for the gravitational energy similar to witten s these include the choice a sqrt r which yields the particularly elegant energy expression first noticed by deser

object matching algorithms using robust hausdorff distance measures a hausdorff distance hd is one of commonly used measures for object matching this work analyzes the conventional hd measures and proposes two robust hd measures based on m estimation and least trimmed square lts which are more efficient than the conventional hd measures by computer simulation the matching performance of the conventional and proposed hd measures is compared with synthetic and real images

hybrid image matching combining hausdorff distance with normalized gradient matching image matching has been a central problem in computer vision and image processing for decades most of the previous approaches to image matching can be categorized into the intensity based and edge based comparison hausdorff distance has been widely used for comparing point sets or edge maps since it does not require point correspondences in this paper we propose a new image similarity measure combining the hausdorff distance with a normalized gradient consistency score for image matching the normalized gradient consistency score is designed to compare the normalized image gradient fields between two images to alleviate the illumination variation problem in image matching by combining the edge based and intensity based information for image matching we are able to achieve robust image matching under different lighting conditions we show the superior robustness property of the proposed image matching technique through experiments on face recognition under different lighting conditions