"Digital human characters are a mainstay of video games, film, and interactive computer graphics applications. However, animating hands remains a challenging aspect of human character animation: posing the hand involves coordinating many degrees of freedom, synthesizing a plausible grasp requires careful placement of contacts, and realistic rendering must account for intricate colour and texture variations. Traditional solutions to these problems require significant manual effort by skilled artists. It is therefore of great interest to computer animation researchers to develop fast and automatic methods for animating hands. This thesis presents methods for improving the realism of hands in real-time physics-based virtual environments.We begin by presenting a framework for skilled motion synthesis, wherein reinforcement learning and non-linear continuous optimization are used to generate controllers for single-handed re-orientation tasks. A mid-level multiphase approach breaks the problem into three parts, providing an appropriate control strategy for each phase and resulting in cyclic finger motions that accomplish the task. The exact trajectory is never specified, as the task goals are concerned with the final orientation and position of the object. Offline simulations are used to learn controller parameters, but the resulting control policy is suitable for real-time applications.We then describe a method for the simulation of compliant articulated structures using an approximate model that focuses on plausible endpoint behaviour. The approach is suitable for simulating physics-based characters under static proportional derivative control and stiff kinematic structures, like robotic grippers. The computation time of the dynamical simulation is reduced by an order of magnitude, and faster than real-time frame rates are easily achieved. Additionally, the state of internal bodies is computed independently, and in a parallel fashion.We also demonstrate an approach for synthesizing colour variation in fingers due to physical interaction with objects. A data-driven model relates contact information to visible colour changes for the fingernail and surrounding tissue on the back of the fingertip. The model construction uses the space of hemoglobin concentrations, as opposed to an RGB colour space, which permits transferability across different fingers and different people. Principal component analysis (PCA) on the sample images results in a compact model, enabling efficient implementation as a fragment shader program.Finally, we introduce a system for capturing grasping and dexterous interactions with real-world objects. A novel sensor ensemble collects information about joint motion and pressure distributions for the hand, and the data is used to design grasping controllers for a physics-based climbing simulation. Additionally, we speculate on how the interaction data can be used to derive future control strategies in physics-based animation. Combining interaction data with physical models is a promising approach for skilled motion synthesis involving hands." --

Physics-based animation is commonplace in animated feature films and even special effects for live-action movies. Think about a recent movie and there will be some sort of special effects such as explosions or virtual worlds. Cloth simulation is no different and is ubiquitous because most virtual characters (hopefully!) wear some sort of clothing. The focus of this book is physics-based cloth simulation. We start by providing background information and discuss a range of applications. This book provides explanations of multiple cloth simulation techniques. More specifically, we start with the most simple explicitly integrated mass-spring model and gradually work our way up to more complex and commonly used implicitly integrated continuum techniques in state-of-the-art implementations. We give an intuitive explanation of the techniques and give additional information on how to efficiently implement them on a computer. This book discusses explicit and implicit integration schemes for cloth simulation modeled with mass-spring systems. In addition to this simple model, we explain the more advanced continuum-inspired cloth model introduced in the seminal work of Baraff and Witkin [1998]. This method is commonly used in industry. We also explain recent work by Liu et al. [2013] that provides a technique to obtain fast simulations. In addition to these simulation approaches, we discuss how cloth simulations can be art directed for stylized animations based on the work of Wojtan et al. [2006]. Controllability is an essential component of a feature animation film production pipeline. We conclude by pointing the reader to more advanced techniques.

The area of simulated human figures is an active research area in computer graphics, and Norman Badler's group at the University of Pennsylvania is one of the leaders in the field. This book summarizes the state of the art in simulating human figures, discusses many of the interesting application areas, and makes some assumptions and predictions about where the field is going.

This book contains the research on modeling bodies, cloth and character based adaptation performed during the last 3 years at MIRALab at the University of Geneva. More than ten researchers have worked together in order to reach a truly 3D Virtual Try On. What we mean by Virtual Try On is the possibility of anyone to give dimensions on her predefined body and obtain her own sized shape body, select a 3D cloth and see oneself animated in Real-Time, walking along a catwalk. Some systems exist today but are unable to adapt to body dimensions, have no real-time animation of body and clothes. A truly system on the web of Virtual Try On does not exist so far. This book is an attempt to explain how to build a 3D Virtual Try On system which is now very much in demand in the clothing industry. To describe this work, the book is divided into five chapters. The first chapter contains a brief historical background of general deformation methods. It ends with a section on the 3D human body scanner systems that are used both for rapid p- totyping and statistical analyses of the human body size variations.

A long-standing goal in computer graphics is to create and control realistic motion for virtual human characters. Despite the progress made over the last decade, it remains challenging to design a system that allows a random user to intuitively create and control life-like human motions. This dissertation focuses on exploring theory, algorithms and applications that enable novice users to quickly and easily create and control natural-looking motions, including both full-body movement and hand articulations, for human characters. More specifically, the goals of this research are: (1) to investigate generative statistical models and physics-based dynamic models to precisely predict how humans move and (2) to demonstrate the utility of our motion models in a wide range of applications including motion analysis, synthesis, editing and acquisition. We have developed two novel generative statistical models from prerecorded motion data and show their promising applications in real time motion editing, online motion control, offline animation design, and motion data processing. In addition, we have explored how to model subtle contact phenomena for dexterous hand grasping and manipulation using physics-based dynamic models. We show for the first time how to capture physically realistic hand manipulation data from ambiguous image data obtained by video cameras. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/149245