Parallelized Incomplete Poisson Preconditioner in Cloth Simulation

Efficient cloth simulation is an important problem for interactive applications that involve virtual humans, such as computer games. A common aspect of many methods that have been developed to simulate cloth is a linear system of equations, which is commonly solved using conjugate gradient or multi-grid approaches. In this paper, we introduce to the computer gaming community a recently proposed preconditioner, the incomplete Poisson preconditioner, for conjugate gradient solvers. We show that the parallelized incomplete Poisson preconditioner (PIPP) performs as well as the current state-of-the-art preconditioners, while being much more amenable to standard thread-level parallelism. We demonstrate our results on an 8-core Apple* Mac* Pro and a 32-core code name Emerald Ridge system

Theoretical Study of the Circuit Architecture of the Basic CFOA and Testing Techniques

This paper examines the closed-loop characteristics of the basic CFOA, and in particular, the dynamic response. Additionally, it also examines the design and advantages of the CFOA regarding its ability to provide a significantly constant closed-loop bandwidth for closed-loop voltage gain. Secondly, the almost limitless slew–rate provided by the class AB input stage that makes it superior to the VOA counterpart. Additionally; this paper also concerns the definitions and measurements of the terminal parameters of the CFOA, regarded as a ‘black box’. It does not deal with the way that these parameters are related to the properties of the active passive and active components of a particular circuit configuration. Simulation is used in terminal parameter determination: this brings with it the facility of using test conditions that would not normally prevail in a laboratory test on silicon implementations of the CFOAs. Thus, we can apply 1mA and 1mV test signals from, respectively, infinite and zero source impedances that range in frequency from d.c to some tens of GHz. Also, we assume the existence of resistors with identical Ohmic value and very high value ideal capacitors. Where appropriate, practical test methods are referred to physical laboratory prototypes

Exporting Vector Muscles for Facial Animation

In this paper we introduce a method of exporting vector muscles from one 3D face to another for facial animation. Starting from a 3D face with an extended version of Waters' linear muscle system, we transfer the linear muscles to a target 3D face. We also transfer the region division, which is used to increase the performance of the muscle as well as to control the animation. The human involvement is just as simple as selecting the faces which shows the most natural facial expressions in the animator's view. The method allows the transfer of the animation to a new 3D model within a short time. The transferred muscles can then be used to create new animations

An investigation on the discrete-time nature of excess phase and jitter

Excess phase in oscillators or phase locked loops is a very important design specification typically modelled as a continuous time signal. In this paper we explain why, when the quantity of interest is jitter, excess phase should be treated as a discrete quantity. This treatment helps explaining noise folding in frequency dividers and analyse its consequences in Phase Locked Loops

Improved designs for current feedback op-amps

The performance of the current feedback op-amps (CFOAs) is very much determined by the input stage of CFOAs, including common-mode rejection ratio (CMRR). Two new CFOAs topologies are presented in this article: one topology uses a cascoding technique, and the second one uses a bootstrapping technique, both of which provide a much better CMRR and lower DC offset voltage than the conventional CFOAs. Moreover, the new CFOAs design exhibits an extended high frequency bandwidth, with a gain accuracy improvement. Applications requiring constant bandwidth with variable (closed loop) gain will benefit from the proposed topologies

Automatic 3D facial model and texture reconstruction from range scans

This paper presents a fully automatic approach to fitting a generic facial model to detailed range scans of human faces to reconstruct 3D facial models and textures with no manual intervention (such as specifying landmarks). A Scaling Iterative Closest Points (SICP) algorithm is introduced to compute the optimal rigid registrations between the generic model and the range scans with different sizes. And then a new template-fitting method, formulated in an optmization framework of minimizing the physically based elastic energy derived from thin shells, faithfully reconstructs the surfaces and the textures from the range scans and yields dense point correspondences across the reconstructed facial models. Finally, we demonstrate a facial expression transfer method to clone facial expressions from the generic model onto the reconstructed facial models by using the deformation transfer technique

Wide-Bandwidth CFOA with High CMRR Performance

​In this paper the authors analyze the conventional current-feedback operational amplifier (CFOA) in terms of common-mode-rejection ratio (CMRR) performance, and having identified the mechanism primarily responsible for the CMRR, they propose two new architecture CFOAs. These new CFOAs are further developed, and modified to provide improved bandwidth, AC gain accuracy and high CMRR performance. The key features of the two proposed new CFOAs are the designs of the internal voltage followers which have two separate biasing currents with a similar dynamic architecture to that of the conventional CFOA. The magnitude of one bias current determines the value of the maximum CMRR, and the second can be used to maximize bandwidth

Analysis and design of a high precision- high output impedance tissue current driver for medical applications

This paper describes the design and operation of a high output impedance tissue current driver circuit, for use in medical electronics, such as Electrical Impedance Tomography (EIT). This novel architecture was designed for implementation in bipolar technology, to meet the specifications for EIT, namely operating frequency range 10 kHz–1 MHz with a target output resistance of 16 MW. Simulation results are presented, showing that the current source more than met the minimum specification for EIT

Recognising facial expressions in video sequences

We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real-time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated to facial expressions are represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold in order to compute a posterior probability associated to a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89\% recognition rate in a set of 333 sequences from the Cohn-Kanade data base

On the Link between Gaussian Homotopy Continuation and Convex Envelopes

Abstract. The continuation method is a popular heuristic in computer vision for nonconvex optimization. The idea is to start from a simpli-fied problem and gradually deform it to the actual task while tracking the solution. It was first used in computer vision under the name of graduated nonconvexity. Since then, it has been utilized explicitly or im-plicitly in various applications. In fact, state-of-the-art optical flow and shape estimation rely on a form of continuation. Despite its empirical success, there is little theoretical understanding of this method. This work provides some novel insights into this technique. Specifically, there are many ways to choose the initial problem and many ways to progres-sively deform it to the original task. However, here we show that when this process is constructed by Gaussian smoothing, it is optimal in a specific sense. In fact, we prove that Gaussian smoothing emerges from the best affine approximation to Vese’s nonlinear PDE. The latter PDE evolves any function to its convex envelope, hence providing the optimal convexification