Dynamic Real-Time Deformations using Space and Time Adaptive Sampling

International audienceThis paper presents the first robust method for animating dynamic visco-elastic deformable objects that provides a guaranteed frame rate. The approach uses an automatic space and time adaptive level of detail technique, in combination with a large-displacement (Green) strain tensor formulation. The body is hierarchically partitioned into a number of tetrahedral regions and mass samples. The local resolution is determined by a quality condition that indicates where and when the resolution is too coarse. As the object moves and deforms, the sampling is refined to concentrate the computational load into the regions that deform the most. Our model consist of a continuous equation solved using a local explicit finite element method. We demonstrate that our adaptive Green strain tensor formulation virtually suppresses unwanted artifacts in the dynamic behavior, compared to adaptive mass-spring and other adaptive approaches. In particular, damped elastic vibration modes are shown to be nearly unchanged for several levels of refinement. Results are presented in the context of a virtual reality system. The user interacts in real-time with the dynamic object (such as a liver) through the control of a rigid tool, attached to a haptic device driven with forces derived from the method.Nous présentons une méthode robuste pour calculer les déformations dynamiques d'objets visco-élastiques, avec une garantie de temps-réel. L'idee maîtresse est d'utiliser une adaptation automatique, dans le temps et dans l'espace, du niveau de détail à laquelle la simulation est calculée, en combinaison avec un modèle élastique autorisant les grands déplacements (tenseur de Green). Le corps déformable est divisé en une hiérarchie de maillages tétrahédraux, du plus grossier aux plus fin. La résolution locale des calculs est déterminée par un critère de qualité qui nous dit quand et où raffiner ou déraffiner le modèle. Lors des déformations, la puissance de calcul se concentre ainsi tout naturellement sur les régions ou les déformations sont les plus grandes. Notre modèle repose sur une équation de l´elasticité des milieux continus, intégrée en utilisant une méthode d'éléments finis explicites. Nous avons montré expérimentalement que notre simulation adaptative basée sur le tenseur de Green supprime les artéfacts du comportement dynamique qui pouvaient être observés lorsque la même méthodologie était appliquée à d'autres modèles (masses-ressorts, tenseur de Cauchy, etc). En particulier, les modes de vibration du matériau semblent sensiblement les mêmes à tous les niveaux de résolution, ce qui s'est révélé indispensable pour faire fonctionner le modèle. Nous présentons nos résultats dans le contexte d'un système de réalité virtuelle ou l'utilisateur intéragit avec l'objet via un outil rigide, contrôlé par une interface à retour d'effort

A survey of real-time crowd rendering

In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft

Real-time Error Control for Surgical Simulation

Objective: To present the first real-time a posteriori error-driven adaptive finite element approach for real-time simulation and to demonstrate the method on a needle insertion problem. Methods: We use corotational elasticity and a frictional needle/tissue interaction model. The problem is solved using finite elements within SOFA. The refinement strategy relies upon a hexahedron-based finite element method, combined with a posteriori error estimation driven local $h$-refinement, for simulating soft tissue deformation. Results: We control the local and global error level in the mechanical fields (e.g. displacement or stresses) during the simulation. We show the convergence of the algorithm on academic examples, and demonstrate its practical usability on a percutaneous procedure involving needle insertion in a liver. For the latter case, we compare the force displacement curves obtained from the proposed adaptive algorithm with that obtained from a uniform refinement approach. Conclusions: Error control guarantees that a tolerable error level is not exceeded during the simulations. Local mesh refinement accelerates simulations. Significance: Our work provides a first step to discriminate between discretization error and modeling error by providing a robust quantification of discretization error during simulations.Comment: 12 pages, 16 figures, change of the title, submitted to IEEE TBM

Spectral analysis for nonstationary audio

A new approach for the analysis of nonstationary signals is proposed, with a focus on audio applications. Following earlier contributions, nonstationarity is modeled via stationarity-breaking operators acting on Gaussian stationary random signals. The focus is on time warping and amplitude modulation, and an approximate maximum-likelihood approach based on suitable approximations in the wavelet transform domain is developed. This paper provides theoretical analysis of the approximations, and introduces JEFAS, a corresponding estimation algorithm. The latter is tested and validated on synthetic as well as real audio signal.Comment: IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, In pres