Building animation tools for fluid-like motions is an important and challenging problem with many applications in computer graphics. The use of physics-based models for fluid flow can greatly assist in creating such tools. Physical models, unlike key frame or procedural based techniques, permit an animator to almost effortlessly create interesting, swirling fluid-like behaviors. Also, the interaction of flows with objects and virtual forces is handled elegantly. Until recently, it was believed that physical fluid models were too expensive to allow real-time interaction. This was largely due to the fact that previous models used unstable schemes to solve the physical equations governing a fluid. In this paper, for the first time, we propose an unconditionally stable model which still produces complex fluid-like flows. As well, our method is very easy to implement. The stability of our model allows us to take larger time steps and therefore achieve faster simulations. We have used our model in conjuction with advecting solid textures to create many fluid-like animations interactively in twoand three-dimensions. CR Categories: I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Animation

Stable fluids

This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

Recent developments in human motion analysis

In this paper, we propose a new approach to numerical smoke simulation for computer graphics applications. The method proposed here exploits physics unique to smoke in order to design a numerical method that is both fast and efficient on the relatively coarse grids traditionally used in computer graphics applications (as compared to the much finer grids used in the computational fluid dynamics literature). We use the inviscid Euler equations in our model, since they are usually more appropriate for gas modeling and less computationally intensive than the viscous Navier-Stokes equations used by others. In addition, we introduce a physically consistent vorticity confinement term to model the small scale rolling features characteristic of smoke that are absent on most coarse grid simulations. Our model also correctly handles the inter-action of smoke with moving objects.

/pdf/visual-simulation-of-smoke-5e6o2k5lr8.pdf

Visual simulation of smoke

http://www2.imm.dtu.dk/projects/manifold/Papers/Vision-based%20human%20motion.pdf

Vision-based human motion analysis: An overview

We present a comprehensive methodology for realistically animating liquid phenomena Our approach unifies existing computer graphics techniques for simulating fluids and extends them by incorporating more complex behavior It is based on the Navier–Stokes equations which couple momentum and mass conservation to completely describe fluid motion Our starting point is an environment containing an arbitrary distribution of fluid, and submerged or semisubmerged obstacles Velocity and pressure are defined everywhere within this environment and updated using a set of finite difference expressions The resulting vector and scalar fields are used to drive a height field equation representing the liquid surface The nature of the coupling between obstacles in the environment and free variables allows for the simulation of a wide range of effects that were not possible with previous computer graphics fluid models Wave effects such as reflection, refraction, and diffraction, as well as rotational effects such as eddies, vorticity, and splashing are a natural consequence of solving the system In addition, the Lagrange equations of motion are used to place buoyant dynamic objects into a scene and track the position of spray and foam during the animation process Typical disadvantages to dynamic simulations such as poor scalability and lack of control are addressed by assuming that stationary obstacles align with grid cells during the finite difference discretization, and by appending terms to the Navier–Stokes equations to include forcing functions Free surfaces in our system are represented as either a collection of massless particles in 2D, or a height field which is suitable for many of the water rendering algorithms presented by researchers in recent years

Realistic animation of liquids

We present a novel approach to the three-dimensional human body model acquisition from three mutually orthogonal views. Our technique is based on the spatiotemporal analysis of the deforming apparent contour of a human moving according to a protocol of movements. For generality and robustness our technique does not use a prior model of the human body and a prior body part segmentation is not assumed. Therefore, our technique applies to humans of any anthropometric dimension. To parameterize and segment over time a deforming apparent contour, we introduce a new shape representation technique based on primitive composition. The composed deformable model allows us to represent large local deformations and their evolution in a compact and intuitive way. In addition, this representation allows us to hypothesize an underlying part structure and test this hypothesis against the relative motion (due to forces exerted from the image data) of the defining primitives of the composed model. Furthermore, we develop a Human Body Part Decomposition Algorithm (HBPDA) that recovers all the body parts of a subject by monitoring the changes over time to the shape of the deforming silhouette. In addition, we modularize the process of simultaneous two-dimensional part determination and shape estimation by employing the Supervisory Control Theory of Discrete Event Systems. Finally, we present a novel algorithm which selectively integrates the (segmented by the HBPDA) apparent contours from three mutually orthogonal viewpoints to obtain a three-dimensional model of the subject‘s body parts. The effectiveness of the approach is demonstrated through a series of experiments where a subject performs a set of movements according to a protocol that reveals the structure of the human body.

Three-Dimensional Human Body Model Acquisition from Multiple Views

PLAYBOT A visually-guided robot for physically disabled children

Recent work in qualitative shape recovery and object recognition has focused on solving the “what is it” problem, while avoiding the “where is it” problem. In contrast, typical CAD-based recognition systems have focused on the “where is it” problem, while assuming they know what the object is. Although each approach addresses an important aspect of the 3-D object recognition problem, each falls short in addressing the complete problem of recognizing and localizing 3-D objects from a large database. In this paper, we first synthesize a new approach to shape recovery for 3-D object recognition that decouples recognition from localization by combining basic elements from these two approaches. Specifically, we use qualitative shape recovery and recognition techniques to provide strong fitting constraints on physics-based deformable model recovery techniques. Secondly, we extend our previously developed technique of fitting deformable models to occluding image contours to the case of image data captured under general orthographic, perspective, and stereo projections. On one hand, integrating qualitative knowledge of the object being fitted to the data, along with knowledge of occlusion supports a much more robust and accurate quantitative fitting. On the other hand, recovering object pose and quantitative surface shape not only provides a richer description for indexing, but supports interaction with the world when object manipulation is required. This paper presents the approach in detail and applies it to real imagery.

/pdf/integrating-qualitative-and-quantitative-shape-recovery-34tu7dkt6q.pdf

Integrating qualitative and quantitative shape recovery

This paper presents a physics-based algorithm for hierarchical shape representation using deformable models with locally adaptive finite elements. Our new adaptive finite element algorithm ensures that during subdivision the desirable finite element mesh generation properties of conformity, non-degeneracy and smoothness are maintained. Through our algorithm, we locally subdivide the triangular finite elements based on the distance between the given datapoints and the model. In this way, we can very efficiently and accurately represent the shape of an object with a resulting small number of model nodes. Furthermore, using our locally adaptive subdivision algorithm in conjunction with our model's global deformations we construct a hierarchical representation of the given 3D data.

/pdf/hierarchical-shape-representation-using-locally-adaptive-17kp0c3lr4.pdf

Dimitri Metaxas

Papers

Realistic animation of liquids

Three-Dimensional Human Body Model Acquisition from Multiple Views

PLAYBOT A visually-guided robot for physically disabled children

Integrating qualitative and quantitative shape recovery

Hierarchical shape representation using locally adaptive finite elements