Preconditioned iterative methods for solving elliptic partial differential equations

Preconditioned iterative methods for solving elliptic partial differential equation

The numerical solution of sparse matrix equations by fast methods and associated computational techniques

The numerical solution of sparse matrix equations by fast methods and associated computational technique

Seventh Copper Mountain Conference on Multigrid Methods

The Seventh Copper Mountain Conference on Multigrid Methods was held on 2-7 Apr. 1995 at Copper Mountain, Colorado. This book is a collection of many of the papers presented at the conference and so represents the conference proceedings. NASA Langley graciously provided printing of this document so that all of the papers could be presented in a single forum. Each paper was reviewed by a member of the conference organizing committee under the coordination of the editors. The multigrid discipline continues to expand and mature, as is evident from these proceedings. The vibrancy in this field is amply expressed in these important papers, and the collection shows its rapid trend to further diversity and depth

Computational Face Recognition Using Machine Learning Models

Faces are among the most complex stimuli that the human visual system processes. Growing commercial interest in face recognition is encouraging, but it also turns out to be a challenging endeavour. These challenges arise when the situations are complex and cause varied facial appearance due to e.g., occlusion, low-resolution, and ageing. The problem of computer-based face recognition using partial facial data is still largely an unexplored area of research and how does computer interpret various parts of the face. Another challenge is age progression and regression, which is considered to be the most revealing topic for understanding the human face changes during life. In this research, the various computational face recognition models are investigated to overcome the challenges posed by ageing and occlusions/partial faces. For partial face-based face recognition, a pre-trained VGGF model is employed for feature extraction and then followed by popular classifiers such as SVMs and Cosine Similarity CS for classification. In this framework, parts of faces such as eyes, nose, forehead, are used individually for training and testing. The results showing that there is an improvement in recognition in small parts, such as recognition rate in forehead enhanced form about 0% to nearly 35%, eyes from about 22% to approximately 65%. In the second framework, five sub-models were built based on Convolutional Neural Networks (CNNs) and those models are named Eyes-CNNs, Nose-CNNs, Mouth-CNNs, Forehead-CNNs, and combined EyesNose-CNNs. The experimental results illustrate a high recognition rate when it comes to small parts, for example, eyes increased up to about 90.83% and forehead reached about 44.5%. Furthermore, the challenge of face ageing is also approached by proposing an age-template based framework, generating an age-based face template for enhanced face generation and recognition. The results showing that generated new aged faces are more reliable comparing with state-of-the-art

New PDE models for imaging problems and applications

Variational methods and Partial Differential Equations (PDEs) have been extensively employed for the mathematical formulation of a myriad of problems describing physical phenomena such as heat propagation, thermodynamic transformations and many more. In imaging, PDEs following variational principles are often considered. In their general form these models combine a regularisation and a data fitting term, balancing one against the other appropriately. Total variation (TV) regularisation is often used due to its edgepreserving and smoothing properties. In this thesis, we focus on the design of TV-based models for several different applications. We start considering PDE models encoding higher-order derivatives to overcome wellknown TV reconstruction drawbacks. Due to their high differential order and nonlinear nature, the computation of the numerical solution of these equations is often challenging. In this thesis, we propose directional splitting techniques and use Newton-type methods that despite these numerical hurdles render reliable and efficient computational schemes. Next, we discuss the problem of choosing the appropriate data fitting term in the case when multiple noise statistics in the data are present due, for instance, to different acquisition and transmission problems. We propose a novel variational model which encodes appropriately and consistently the different noise distributions in this case. Balancing the effect of the regularisation against the data fitting is also crucial. For this sake, we consider a learning approach which estimates the optimal ratio between the two by using training sets of examples via bilevel optimisation. Numerically, we use a combination of SemiSmooth (SSN) and quasi-Newton methods to solve the problem efficiently. Finally, we consider TV-based models in the framework of graphs for image segmentation problems. Here, spectral properties combined with matrix completion techniques are needed to overcome the computational limitations due to the large amount of image data. Further, a semi-supervised technique for the measurement of the segmented region by means of the Hough transform is proposed

CAD-Based Porous Scaffold Design of Intervertebral Discs in Tissue Engineering

With the development and maturity of three-dimensional (3D) printing technology over the past decade, 3D printing has been widely investigated and applied in the field of tissue engineering to repair damaged tissues or organs, such as muscles, skin, and bones, Although a number of automated fabrication methods have been developed to create superior bio-scaffolds with specific surface properties and porosity, the major challenges still focus on how to fabricate 3D natural biodegradable scaffolds that have tailor properties such as intricate architecture, porosity, and interconnectivity in order to provide the needed structural integrity, strength, transport, and ideal microenvironment for cell- and tissue-growth. In this dissertation, a robust pipeline of fabricating bio-functional porous scaffolds of intervertebral discs based on different innovative porous design methodologies is illustrated. Firstly, a triply periodic minimal surface (TPMS) based parameterization method, which has overcome the integrity problem of traditional TPMS method, is presented in Chapter 3. Then, an implicit surface modeling (ISM) approach using tetrahedral implicit surface (TIS) is demonstrated and compared with the TPMS method in Chapter 4. In Chapter 5, we present an advanced porous design method with higher flexibility using anisotropic radial basis function (ARBF) and volumetric meshes. Based on all these advanced porous design methods, the 3D model of a bio-functional porous intervertebral disc scaffold can be easily designed and its physical model can also be manufactured through 3D printing. However, due to the unique shape of each intervertebral disc and the intricate topological relationship between the intervertebral discs and the spine, the accurate localization and segmentation of dysfunctional discs are regarded as another obstacle to fabricating porous 3D disc models. To that end, we discuss in Chapter 6 a segmentation technique of intervertebral discs from CT-scanned medical images by using deep convolutional neural networks. Additionally, some examples of applying different porous designs on the segmented intervertebral disc models are demonstrated in Chapter 6

Computational Aspects of Heat Transfer in Structures

Techniques for the computation of heat transfer and associated phenomena in complex structures are examined with an emphasis on reentry flight vehicle structures. Analysis methods, computer programs, thermal analysis of large space structures and high speed vehicles, and the impact of computer systems are addressed

Implicit muscle models for interactive character skinning

En animation de personnages 3D, la déformation de surface, ou skinning, est une étape cruciale. Son rôle est de déformer la représentation surfacique d'un personnage pour permettre son rendu dans une succession de poses spécifiées par un animateur. La plausibilité et la qualité visuelle du résultat dépendent directement de la méthode de skinning choisie. Sa rapidité d'exécution et sa simplicité d'utilisation sont également à prendre en compte pour rendre possible son usage interactif lors des sessions de production des artistes 3D. Les différentes méthodes de skinning actuelles se divisent en trois catégories. Les méthodes géométriques sont rapides et simples d'utilisation, mais leur résultats manquent de plausibilité. Les approches s'appuyant sur des exemples produisent des résultats réalistes, elles nécessitent en revanche une base de données d'exemples volumineuse, et le contrôle de leur résultat est fastidieux. Enfin, les algorithmes de simulation physique sont capables de modéliser les phénomènes dynamiques les plus complexes au prix d'un temps de calcul souvent prohibitif pour une utilisation interactive. Les travaux décrits dans cette thèse s'appuient sur Implicit Skinning, une méthode géométrique corrective utilisant une représentation implicite des surfaces, qui permet de résoudre de nombreux problèmes rencontrés avec les méthodes géométriques classiques, tout en gardant des performances permettant son usage interactif. La contribution principale de ces travaux est un modèle d'animation qui prend en compte les effets des muscles des personnages et de leur interactions avec d'autres éléments anatomiques, tout en bénéficiant des avantages apportés par Implicit Skinning. Les muscles sont représentés par une surface d'extrusion le long d'axes centraux. Les axes des muscles sont contrôlés par une méthode de simulation physique simplifiée. Cette représentation permet de modéliser les collisions des muscles entre eux et avec les os, d'introduire des effets dynamiques tels que rebonds et secousses, tout en garantissant la conservation du volume, afin de représenter le comportement réel des muscles. Ce modèle produit des déformations plus plausibles et dynamiques que les méthodes géométriques de l'état de l'art, tout en conservant des performances suffisantes pour permettre son usage dans une session d'édition interactive. Elle offre de plus aux infographistes un contrôle intuitif sur la forme des muscles pour que les déformations obtenues se conforment à leur vision artistique.Surface deformation, or skinning is a crucial step in 3D character animation. Its role is to deform the surface representation of a character to be rendered in the succession of poses specified by an animator. The quality and plausiblity of the displayed results directly depends on the properties of the skinning method. However, speed and simplicity are also important criteria to enable their use in interactive editing sessions. Current skinning methods can be divided in three categories. Geometric methods are fast and simple to use, but their results lack plausibility. Example-based approaches produce realistic results, yet they require a large database of examples while remaining tedious to edit. Finally, physical simulations can model the most complex dynamical phenomena, but at a very high computational cost, making their interactive use impractical. The work presented in this thesis are based on, Implicit Skinning, is a corrective geometric approach using implicit surfaces to solve many issues of standard geometric skinning methods, while remaining fast enough for interactive use. The main contribution of this work is an animation model that adds anatomical plausibility to a character by representing muscle deformations and their interactions with other anatomical features, while benefiting from the advantages of Implicit Skinning. Muscles are represented by an extrusion surface along a central axis. These axes are driven by a simplified physics simulation method, introducing dynamic effects, such as jiggling. The muscle model guarantees volume conservation, a property of real-life muscles. This model adds plausibility and dynamics lacking in state-of-the-art geometric methods at a moderate computational cost, which enables its interactive use. In addition, it offers intuitive shape control to animators, enabling them to match the results with their artistic vision