Modelling the Car Seated Human Body using Composite Ellipsoidal Bodies and Evaluation of Size and Shape Specific Stiffness Data for Various Human Segments

Automobile is one of the primary modes of worldwide transport system, which must offer highest level of health, safety and comfort levels for the occupants inside. Health, safety and comfort of any moving vehicle and its human occupants are mainly characterized by the level of the vibration generated inside the human body. With the development of modern computer based technologies, over last few decades computerized simulations have been gaining huge importance to anticipate the level of vibration generated inside the automotive seated human body. Many simulation based research works had been conducted in past to predict the effect of vibration inside automotive-human assembly, though one of the key parameters to define the simulation set up, namely stiffness values of different human segments; had been collected from past relevant research studies or available testing data resources, which overlooked the real shapes and sizes of the human portions, hence, lacking the practical feasibility. In this research paper, a simplified car seated human made of ellipsoidal segments has been proposed. The segmental dimensions and masses have been extracted from anthropometric database and later, the formulations for composite fibre-matrix configuration have been implemented. A systematic approach has been outlined to evaluate the three-dimensional stiffness values for all the human portions. The obtained stiffness values have been validated by comparing to the data obtained from similar kind of investigations and test results

Composite Generalized Elliptic Curve-Based Surface Reconstruction

Cross-section curves play an important role in many fields. Analytically representing cross-section curves can greatly reduce design variables and related storage costs and facilitate other applications. In this paper, we propose composite generalized elliptic curves to approximate open and closed cross-section curves, present their mathematical expressions, and derive the mathematical equations of surface reconstruction from composite generalized elliptic curves. The examples given in this paper demonstrate the effectiveness and high accuracy of the proposed method. Due to the analytical nature of composite generalized elliptic curves and the surfaces reconstructed from them, the proposed method can reduce design variables and storage requirements and facilitate other applications such as level of detail

Tracking and modelling motion for biomechanical analysis

This thesis focuses on the problem of determining appropriate skeletal configurations for which a virtual animated character moves to desired positions as smoothly, rapidly, and as accurately as possible. During the last decades, several methods and techniques, sophisticated or heuristic, have been presented to produce smooth and natural solutions to the Inverse Kinematics (IK) problem. However, many of the currently available methods suffer from high computational cost and production of unrealistic poses. In this study, a novel heuristic method, called Forward And Backward Reaching Inverse Kinematics (FABRIK), is proposed, which returns visually natural poses in real-time, equally comparable with highly sophisticated approaches. It is capable of supporting constraints for most of the known joint types and it can be extended to solve problems with multiple end effectors, multiple targets and closed loops. FABRIK was compared against the most popular IK approaches and evaluated in terms of its robustness and performance limitations. This thesis also includes a robust methodology for marker prediction under multiple marker occlusion for extended time periods, in order to drive real-time centre of rotation (CoR) estimations. Inferred information from neighbouring markers has been utilised, assuming that the inter-marker distances remain constant over time. This is the first time where the useful information about the missing markers positions which are partially visible to a single camera is deployed. Experiments demonstrate that the proposed methodology can effectively track the occluded markers with high accuracy, even if the occlusion persists for extended periods of time, recovering in real-time good estimates of the true joint positions. In addition, the predicted positions of the joints were further improved by employing FABRIK to relocate their positions and ensure a fixed bone length over time. Our methodology is tested against some of the most popular methods for marker prediction and the results confirm that our approach outperforms these methods in estimating both marker and CoR positions. Finally, an efficient model for real-time hand tracking and reconstruction that requires a minimum number of available markers, one on each finger, is presented. The proposed hand model is highly constrained with joint rotational and orientational constraints, restricting the fingers and palm movements to an appropriate feasible set. FABRIK is then incorporated to estimate the remaining joint positions and to fit them to the hand model. Physiological constraints, such as inertia, abduction, flexion etc, are also incorporated to correct the final hand posture. A mesh deformation algorithm is then applied to visualise the movements of the underlying hand skeleton for comparison with the true hand poses. The mathematical framework used for describing and implementing the techniques discussed within this thesis is Conformal Geometric Algebra (CGA)

Efficient and detailed sketch-based character modelling with composite generalized elliptic curves and ODE surface creators.

Sketch-based modelling (SBM), dating back to 1980s, has attracted a lot of researches’ attention due to its easy-to-use features and high efficiency in generating 3D models. However, existing sketch-based modelling approaches are incapable in creating detailed and realistic 3D character models. This project aims to propose new techniques which can create more detailed 3D character models with easiness and efficiency. The basic idea is to fit primitives to the sketches consisting of front view contours, side view contours and cross-section curves to obtain more detailed shape, propose ODE (ordinary differential equation) driven deformation to create more realistic shapes, and use surfaces defined by cross-sectional curves to represent sketch-based and ODE-driven 3D character models. In order to achieve the above aim, this thesis firstly investigates curve fitting of cross-sectional shapes and solved the problem of representing cross-sectional curves with generalized ellipses or composite generalized elliptic segments. Then, this thesis proposes a new mathematical formula for defining a surface from the cross-sectional curves. A new sketch-guided and ODE-driven character modelling technique is proposed, consisting of two main components: primitive deformer and detail generator. With such a technique, I first draw 2D silhouette contours of a character model. Then, I select proper primitives and align them with the corresponding silhouette contours. After that, I develope a sketch-guided and ODE-driven primitive deformer. It uses ODE-based deformations to deform the cross-section curves of the primitive to exactly match the generated 2D silhouette contours in one view plane and with the curve-fitting method and surface re-construction method mentioned above, a base mesh of a character model consisting of deformed primitive is obtained. In order to add various 3D details, I develop a local shape generator which uses sketches in different view planes to define a local shape and employs ODE-driven deformations to create a local surface passing through all the sketches. The experimental results demonstrate that the proposed approach can create 3D character models with 3D details from 2D sketches easily, quickly and precisely. Cross-section contours are important in defining cross-section shapes and creating detailed models. In order to develop a cross-section contour- based modelling approach, how to mathematically represent cross-section curves must be first solved. The second aim of this project is to propose composite generalized elliptic curves and introduce them into character modelling to achieve an analytical and compact mathematical representation of cross-section contours. Current template-based character modelling which creates 3D character models from sketches retrieves and then uses 3D template models directly. Since retrieving 3D models from sketches is not an easy task, the third aim of this project is to extract 2D cross-section contours from template models and use the extracted 2D cross section contours as templates to assist the creation of 3D character models for simplifying and accelerating the modelling process. Although there are many different approaches to interpret shapes with sketch strokes, but to our knowledge, no one utilises 2D template cross-section contours to quickly generate the shapes of human characters in a sketch-based system, which is one of the contributions of this project

From Image-based Motion Analysis to Free-Viewpoint Video

The problems of capturing real-world scenes with cameras and automatically analyzing the visible motion have traditionally been in the focus of computer vision research. The photo-realistic rendition of dynamic real-world scenes, on the other hand, is a problem that has been investigated in the field of computer graphics. In this thesis, we demonstrate that the joint solution to all three of these problems enables the creation of powerful new tools that are benecial for both research disciplines. Analysis and rendition of real-world scenes with human actors are amongst the most challenging problems. In this thesis we present new algorithmic recipes to attack them. The dissertation consists of three parts: In part I, we present novel solutions to two fundamental problems of human motion analysis. Firstly, we demonstrate a novel hybrid approach for markerfree human motion capture from multiple video streams. Thereafter, a new algorithm for automatic non-intrusive estimation of kinematic body models of arbitrary moving subjects from video is detailed. In part II of the thesis, we demonstrate that a marker-free motion capture approach makes possible the model-based reconstruction of free-viewpoint videos of human actors from only a handful of video streams. The estimated 3D videos enable the photo-realistic real-time rendition of a dynamic scene from arbitrary novel viewpoints. Texture information from video is not only applied to generate a realistic surface appearance, but also to improve the precision of the motion estimation scheme. The commitment to a generic body model also allows us to reconstruct a time-varying reflectance description of an actor`s body surface which allows us to realistically render the free-viewpoint videos under arbitrary lighting conditions. A novel method to capture high-speed large scale motion using regular still cameras and the principle of multi-exposure photography is described in part III. The fundamental principles underlying the methods in this thesis are not only applicable to humans but to a much larger class of subjects. It is demonstrated that, in conjunction, our proposed algorithmic recipes serve as building blocks for the next generation of immersive 3D visual media.Die Entwicklung neuer Algorithmen zur optischen Erfassung und Analyse der Bewegung in dynamischen Szenen ist einer der Forschungsschwerpunkte in der computergestützten Bildverarbeitung. Während im maschinellen Bildverstehen das Augenmerk auf der Extraktion von Informationen liegt, konzentriert sich die Computergrafik auf das inverse Problem, die fotorealistische Darstellung bewegter Szenen. In jüngster Vergangenheit haben sich die beiden Disziplinen kontinuierlich angenähert, da es eine Vielzahl an herausfordernden wissenschaftlichen Fragestellungen gibt, die eine gemeinsame Lösung des Bilderfassungs-, des Bildanalyse- und des Bildsyntheseproblems verlangen. Zwei der schwierigsten Probleme, welche für Forscher aus beiden Disziplinen eine große Relevanz besitzen, sind die Analyse und die Synthese von dynamischen Szenen, in denen Menschen im Mittelpunkt stehen. Im Rahmen dieser Dissertation werden Verfahren vorgestellt, welche die optische Erfassung dieser Art von Szenen, die automatische Analyse der Bewegungen und die realistische neue Darstellung im Computer erlauben. Es wid deutlich werden, dass eine Integration von Algorithmen zur Lösung dieser drei Probleme in ein Gesamtsystem die Erzeugung völlig neuartiger dreidimensionaler Darstellungen von Menschen in Bewegung ermöglicht. Die Dissertation ist in drei Teile gegliedert: Teil I beginnt mit der Beschreibung des Entwurfs und des Baus eines Studios zur zeitsynchronen Erfassung mehrerer Videobildströme. Die im Studio aufgezeichneten Multivideosequenzen dienen als Eingabedaten für die im Rahmen dieser Dissertation entwickelten videogestützten Bewegunsanalyseverfahren und die Algorithmen zur Erzeugung dreidimensionaler Videos. Im Anschluß daran werden zwei neu entwickelte Verfahren vorgestellt, die Antworten auf zwei fundamentale Fragen in der optischen Erfassung menschlicher Bewegung geben, die Messung von Bewegungsparametern und die Erzeugung von kinematischen Skelettmodellen. Das erste Verfahren ist ein hybrider Algorithmus zur markierungslosen optischen Messung von Bewegunsgparametern aus Multivideodaten. Der Verzicht auf optische Markierungen wird dadurch ermöglicht, dass zur Bewegungsanalyse sowohl aus den Bilddaten rekonstruierte Volumenmodelle als auch leicht zu erfassende Körpermerkmale verwendet werden. Das zweite Verfahren dient der automatischen Rekonstruktion eines kinematischen Skelettmodells anhand von Multivideodaten. Der Algorithmus benötigt weder optischen Markierungen in der Szene noch a priori Informationen über die Körperstruktur, und ist in gleicher Form auf Menschen, Tiere und Objekte anwendbar. Das Thema das zweiten Teils dieser Arbeit ist ein modellbasiertes Verfahrenzur Rekonstruktion dreidimensionaler Videos von Menschen in Bewegung aus nur wenigen zeitsynchronen Videoströmen. Der Betrachter kann die errechneten 3D Videos auf einem Computer in Echtzeit abspielen und dabei interaktiv einen beliebigen virtuellen Blickpunkt auf die Geschehnisse einnehmen. Im Zentrum unseres Ansatzes steht ein silhouettenbasierter Analyse-durch-Synthese Algorithmus, der es ermöglicht, ohne optische Markierungen sowohl die Form als auch die Bewegung eines Menschen zu erfassen. Durch die Berechnung zeitveränderlicher Oberächentexturen aus den Videodaten ist gewährleistet, dass eine Person aus jedem beliebigen Blickwinkel ein fotorealistisches Erscheinungsbild besitzt. In einer ersten algorithmischen Erweiterung wird gezeigt, dass die Texturinformation auch zur Verbesserung der Genauigkeit der Bewegunsgssch ätzung eingesetzt werden kann. Zudem ist es durch die Verwendung eines generischen Körpermodells möglich, nicht nur dynamische Texturen sondern sogar dynamische Reektionseigenschaften der Körperoberäche zu messen. Unser Reektionsmodell besteht aus einer parametrischen BRDF für jeden Texel und einer dynamischen Normalenkarte für die gesamte Körperoberäche. Auf diese Weise können 3D Videos auch unter völlig neuen simulierten Beleuchtungsbedingungen realistisch wiedergegeben werden. Teil III dieser Arbeit beschreibt ein neuartiges Verfahren zur optischen Messung sehr schneller Bewegungen. Bisher erforderten optische Aufnahmen von Hochgeschwindigkeitsbewegungen sehr teure Spezialkameras mit hohen Bildraten. Im Gegensatz dazu verwendet die hier beschriebene Methode einfache Digitalfotokameras und das Prinzip der Multiblitzfotograe. Es wird gezeigt, dass mit Hilfe dieses Verfahrens sowohl die sehr schnelle artikulierte Handbewegung des Werfers als auch die Flugparameter des Balls während eines Baseballpitches gemessen werden können. Die hochgenau erfaßten Parameter ermöglichen es, die gemessene Bewegung in völlig neuer Weise im Computer zu visualisieren. Obgleich die in dieser Dissertation vorgestellten Verfahren vornehmlich der Analyse und Darstellung menschlicher Bewegungen dienen, sind die grundlegenden Prinzipien auch auf viele anderen Szenen anwendbar. Jeder der beschriebenen Algorithmen löst zwar in erster Linie ein bestimmtes Teilproblem, aber in Ihrer Gesamtheit können die Verfahren als Bausteine verstanden werden, welche die nächste Generation interaktiver dreidimensionaler Medien ermöglichen werden

Level-Set-XFEM-Density Topology Optimization of Active Structures: Methods and Applications

To unlock the potential of advanced manufacturing technologies like additive manufacturing, an inherent need for sophisticated design tools exists. In this thesis, a systematic approach for designing printed active structures using a combined level-set (LS) extended finite element (XFEM) density topology optimization (TO) scheme is developed. This combined scheme alleviates the downsides of both LS and density based TO approaches while building upon the advantages of either method. Thus, a superior design optimization approach is created, which, when coupled with the XFEM, yields a highly accurate physical modeling method. The unique capabilities of this combined approach include hole nucleation and minimum feature size control while retaining a crisp and unambiguous definition of the material interface. Different stabilization and regularization schemes are developed to maximize the robustness of the proposed method. Ensuring sufficient numerical stability during the TO process is especially critical when using large deformation nonlinear elasticity models. Without sufficient stabilization, divergence in the analysis or optimization process is frequently encountered. Therefore, a novel explicit LS regularization scheme, based on the construction of a signed distance field (SDF) for every design iteration, is developed in this thesis. It is also demonstrated that the obtained SDF can be used for minimum feature size control and control of the mean curvature during a TO process. Numerical design examples in 2D and 3D are presented to demonstrate the applicability of the proposed combined TO method. Physical specimens of 4D printed samples are used to validate the accuracy of the predicted structural performance by the developed thermomechanical large-strain XFEM model. Finally, conclusions and recommendations for future work are presented and the original contributions made in this thesis are summarized

Automatic skeletonization and skin attachment for realistic character animation.

The realism of character animation is associated with a number of tasks ranging from modelling, skin defonnation, motion generation to rendering. In this research we are concerned with two of them: skeletonization and weight assignment for skin deformation. The fonner is to generate a skeleton, which is placed within the character model and links the motion data to the skin shape of the character. The latter assists the modelling of realistic skin shape when a character is in motion. In the current animation production practice, the task of skeletonization is primarily undertaken by hand, i.e. the animator produces an appropriate skeleton and binds it with the skin model of a character. This is inevitably very time-consuming and costs a lot of labour. In order to improve this issue, in this thesis we present an automatic skeletonization framework. It aims at producing high-quality animatible skeletons without heavy human involvement while allowing the animator to maintain the overall control of the process. In the literature, the tenn skeletonization can have different meanings. Most existing research on skeletonization is in the remit of CAD (Computer Aided Design). Although existing research is of significant reference value to animation, their downside is the skeleton generated is either not appropriate for the particular needs of animation, or the methods are computationally expensive. Although some purpose-build animation skeleton generation techniques exist, unfortunately they rely on complicated post-processing procedures, such as thinning and pruning, which again can be undesirable. The proposed skeletonization framework makes use of a new geometric entity known as the 3D silhouette that is an ordinary silhouette with its depth information recorded. We extract a curve skeleton from two 3D silhouettes of a character detected from its two perpendicular projections. The skeletal joints are identified by down sampling the curve skeleton, leading to the generation of the final animation skeleton. The efficiency and quality are major performance indicators in animation skeleton generation. Our framework achieves the former by providing a 2D solution to the 3D skeletonization problem. Reducing in dimensions brings much faster performances. Experiments and comparisons are carried out to demonstrate the computational simplicity. Its accuracy is also verified via these experiments and comparisons. To link a skeleton to the skin, accordingly we present a skin attachment framework aiming at automatic and reasonable weight distribution. It differs from the conventional algorithms in taking topological information into account during weight computation. An effective range is defined for a joint. Skin vertices located outside the effective range will not be affected by this joint. By this means, we provide a solution to remove the influence of a topologically distant, hence highly likely irrelevant joint on a vertex. A user-defined parameter is also provided in this algorithm, which allows different deformation effects to be obtained according to user's needs. Experiments and comparisons prove that the presented framework results in weight distribution of good quality. Thus it frees animators from tedious manual weight editing. Furthermore, it is flexible to be used with various deformation algorithms