April 20, 2019

Numerical and Computational Challenges in Science and Engineering

Workshop on the Mathematics of Computer Animation
November 8-9, 2002


Wayne H. Enright, Department of Computer Science, University of Toronto

Fast Visualization/Animation of Approximate Solutions of PDEs
Visualizing and displaying approximate solutions of PDEs on high resolution screens and other devices has become a significant part of scientific computation. On the other hand the prime focus of numerical analysts has been and still is on the development of effective numerical methods for generating accurate approximate solutions on relatively coarse meshes (covering the domain of interest). In order to display or visualize the results of such methods at the resolution required by the current display devices significant computational effort is often required and we are investigating efficient algorithms for carrying out these tasks.

In this presentation we will consider the efficient generation of contour plots and suface plots and the use of animation. We have developed and implemented (in MATLAB) an approach that directly generates surface plots and contour lines associated with a function $u(x,y)$ that does not have to solve a PDE on a fine mesh.
Our approach exploits knowledge of an underlying PDE to define a multivariate piecewise polynomial on a coarse unstructured mesh. This piecewise polynomial can then be used to generate accurate off-mesh data (in particular data required for effective visualization).We will show how this allows us to generate animated contour plots at a much lower cost than that involved in generating animated surface plots. Examples will be presented to show the effectiveness of this approach on a variety of realistic problems.


Jessica Hodgins, School of Computer Science, Carnegie Mellon University

Animating Human Characters
Computer animations and virtual environments both require a controllable source of motion for their characters. Two possible solutions are simulation and motion capture and over the past 10 years, we have explored both techniques separately. For example, we developed control algorithms that allow rigid body models to run or bicycle, bounce on a trampoline, and perform a handspring vault. More recently we explored several interfaces for controlling a avatar animated from a database of motion capture data. Recently, we have begun to combine simulations with motion capture data in the hope that these techniques will benefit both from the physical realism of simulation and from the humanlike motion provided by captured data.


Jessica Hodgins joined the Robotics Institute and Computer Science Department at Carnegie Mellon University as a Associate Professor in fall of 2000. Prior to moving to CMU, she was an an Associate Professor and Assistant Dean in the College of Computing at Georgia
Institute of Technology. She received her Ph.D. in Computer Science from Carnegie Mellon University in 1989. Her research focuses on computer graphics, animation, and robotics. She has received a NSF Young Investigator Award, a Packard Fellowship, and a Sloan Fellowship. She is editor-in-chief of ACM Transactions on Graphics and will be SIGGRAPH Papers Chair in 2003.


James Kuffner, School of Computer Science, Carnegie Mellon University

Task-level Character Motion Synthesis as High-dimensional Search
Gross body motions for animated characters can be represented by time-parameterized function curves in the joint configuration space. The problem of automatically synthesizing animation for characters can then be formulated as a discrete search over a continuous, high-dimensional configuration space for a motion trajectory that satisfies a number of constraints. The constraints on the motion can arise from joint limits, obstacles in the world, self-collisions, body physics, or aesthetic considerations such as naturalness and style. This talk considers the application of robot motion planning techniques to the problem of automatic motion synthesis for articulated characters. Key research issues will be discussed along with demonstrations of interactive, task-based control interfaces for character navigation, object manipulation, and full-body motions.


Chris Landreth

Realism and Psychology in Animation
The notion that computer graphics can recreate 'photorealistic' reality had been an ongoing fetish in the industry since its inception a generation ago. And in spite of its use, or more likely because of it, it is largely perceived as a sterile, impersonal, crass, perhaps even menacing medium. Why?

Part of the answer, in my opinion, is that CG artists are not yet exploring another sort of realism that CGI can show--the realism of human thoughts, emotions, and psychological nuances. What I'm interested in is not achieving 'photorealism' per se, but coopting elements of photorealism to recreate the realism of the complex, chaotic, conflicted, sometimes mundane and always glorious mess that we call "human nature". How can one capture that mathematically?

I will show examples of how "Psychorealism" has been explored in animation, including my short films "the end" and "Bingo". I will talk a bit about the emerging animation form of the 'animated documentary', and my current project, an animated documentary "Ryan", based on the life of the Canadian animator Ryan Larkin.

Raghu Machiraju, The Ohio State University

Synthesis and Animation Through Analysis of Data
Visualization and data analysis can allow for the systematic detection of features. For example, features like vortices in a flow field can be detected using efficient and robust methods derived from the physics of the problem. Similarly, discrete simulation models can be used to generate phenomena. These methods can generate rough looking surfaces are amenable to user control.

Animation has relied on the direct numerical simulation of phenomenon. It is often hard to achieve to allow interactive control. Perhaps, one could use results from visualization and discrete simulation in an inverse fashion to generate necessary imagery. I will first describe our recent work in visualization and modeling and then conclude with some thoughts for using the same towards animation.

Dinesh K. Pai, Division of Computer and Information Sciences, Rutgers University

Multisensory Interactive Animation
Humans experience the world with all their senses, including vision, touch, and hearing. I will describe recent progress in my group towards constructing multisensory animations with integrated graphics, haptics, and sounds. The animations are based on interactive simulation of physically based models, and provide the immediacy of interacting with the real world. I will describe how we can construct mathematical models suitable for multisensory simulation, and reality based modeling using the UBC Active Measurement Facility (ACME) and the new Rutgers Haptic, Auditory, and Visual Environment.

Dinesh K. Pai is a Professor in the Department of Computer Science at Rutgers, the State University of NJ. He is also a Professor at the University of British Columbia and a fellow of the BC Advanced Systems Institute. He received his Ph.D. from Cornell University, Ithaca, NY. His research interests span the areas of graphics, robotics, and multisensory human-computer interaction. One current research focus is reality-based modeling, i.e., building multisensory computational models of the physical world from measurements. This includes a recent thrust in reconstruction from medical ultrasound images. Another focus is fast simulation with integrated sound, haptics, and graphics, especially simulation of contact.

Rick Parent, Department of Computer and Information Science, Ohio State University

Lip-sync Animation
Human speech is complex. The main visible articulators, the lips and tongue, are deformable. The muscles which drive speech produce visible secondary effects which convey meaning. Speech is context dependent and is changed by intent and emotion. Incorporating all of this into a computational model for the visual aspects of speech is a challenging task and will be discussed.


Nancy Pollard, Brown University
Animating Manipulation Tasks from Human Motion Data
Captured human motion data has been used to create convincing human motion for a wide variety of tasks including locomotion, sports, and dance. However, generalizing motion capture data to new situations remains difficult, and tasks that involve manipulating objects in the virtual world are rarely addressed. This talk considers the problem of adapting a motion capture data for a quasistatic manipulation task to new object geometries and friction conditions. I will argue that correct physics is critical for this type of task and will present an algorithm that generates manipulation plans for new objects by using the captured motion data to constrain the solution space to a set of plans physically similar to the original. Our planner provides guarantees on maximum task forces and flexibility in contact placement and works for a wide range of object geometries and coefficients of friction. I will show results for the task of tumbling large, heavy objects. We have demonstrated these results with a humanoid robot as well as with animated characters.

Michiel van de Panne, University of British Columbia

Haptic control envelopes and other unfinished projects
Animation tools are perhaps at their best when they neither over-constrain nor under-constrain the motions to be created. After discussing some of the types of constraints that of possible use in defining animated motion, I will present some recent experiments with interactive systems that enforce different types of computable constraints. I'll describe other unfinished projects and unsolved problems as time allows.

Back to top