In this article we describe our approach to generating convincing and empathetic facial animation. Our goal is to develop a robust facial animation platform that is usable and can be easily extended. We also want to facilitate the integration of research in the area and to directly incorporate the characters in interactive applications such as embodied conversational agents and games. We have developed a framework capable of easily animating MPEG-4 parameterized faces through highlevel description of facial actions and behaviors. The animations can be generated in real time for interactive applications. We present some case studies that integrate computer vision techniques in order to provide interaction between the user and a character that interacts with different facial actions according to events in the application.

The Circle of Willis (COW) is a circle of arteries at the base of the brain, formed by the junction of the basilar, posterior cerebral, internal carotid and anterior cerebral arteries (see figure 1.1). According to Weir et al [166], an aneurysm is a dilation of an artery caused by the vessel wall yielding and stretching due to the pressure of the blood. Initially

BackgroundProtein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors’ real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF).ResultsThe use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner.ConclusionsProtein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor’s binding site. Utilization of the intrinsic flexibility of Mtb’s InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb’s InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

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In this paper we present a platform called VhCVE, in which relevant issues related to Collaborative Virtual Environments applications are integrated. The main goal is to provide a framework where participants can interact with others by voice and chat. Also, manipulation tools such as a mouse using Computer Vision and Physics are included, as well as rendering techniques (e.g. light sources, shadows and weather effects). In addition, avatar animation in terms of face and body motion is provided. Results indicate that our platform can be used as a interactive virtual world to help communication among people.