Table Of ContentSeries Editors
w.
Hansmann
W. Purgathofer
F. Sillion
N. Magnenat -Thalmann
D. Thalmann (eds.)
Computer Animation
and Simulation 2001
Proceedings of the Eurographics Workshop
in Manchester, UK,
September 2-3,2001
Eurographics
Springer-Verlag Wien GmbH
Prof. Dr. Nadia Magnenat- Thalmann
MIRA Laboratory
University of Geneva
Geneva, Switzerland
Dr. Daniel Thalmann
Computer Graphics Laboratory
Swiss Federal Institute of Technology
Lausanne, Switzerland
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© 2001 Springer-Verlag Wien
Originally published by Springer-Verlag/Wien in 2001
Typesetting: Camera-ready by authors
Printed on acid-free and chlorine-free bleached paper
SPIN: 10847739
With 79 partly coloured Figures
ISSN 0946-2767
ISBN 978-3-211-83711-5 ISBN 978-3-7091-6240-8 (eBook)
DOI 10.1007/978-3-7091-6240-8
Preface
This volume contains the research papers presented at the 12th Eurographics
Workshop on Computer Animation and Simulation, Manchester, UK, September 2-3,
2001.
The workshop is an international forum for research in computer-animation and
simulation. This year, we choose to give a special focus on the modelling and
animation of complex phenomena. This includes the modelling of virtual creatures -
from their body-parts to the control of their behavior, and the animation of natural
phenomena such as water, smoke, fire and vegetation.
The call for papers required submission of the full papers for review, and each paper
was reviewed by at least 2 members of the international program committee and
additional reviewers. Based on the reviews, 16 papers were accepted. We added to the
final program an invited talk by Jos Stam.
We wish to thank all reviewers for their time and effort in working within the rigid
constraints of the tight schedule, thereby making it possible to publish this volume in
time for the workshop. We also thank the authors for their contributions to the
workshop, without whom this unique forum for animation and simulation work
would not exist.
We are grateful to the Eurographics Association and especially to Werner Purgathofer
from the Technical University of Vienna, for his support in publishing the workshop
as a volume of the Springer-Verlag Eurographics Series. We also thank the
Eurographics '2001 organisers, especially Roger Hubbold, and Heinrich Muller from
the EO board. We are also very grateful to Zerrin Celebi for the organization of the
review process.
Marie-Paule Cani
Nadia Magnenat -Thalmann
Daniel Thalmann
Program Committee
Marie-Paule Cani (iMAGIS INP Grenoble, France)
Nadia Magnenat-Thalmann (University of Geneva, Switzerland)
Daniel Thalmann (EPFL, Lausanne, Switzerland)
Bruno Arnaldi (IRIS A, Rennes, France)
Norm Badler (University of Pennsylvania, USA)
Ronan Boulic (EPFL, Lausanne, Switzerland)
Michael Cohen (Microsoft, Seattle, USA)
Mathieu Desbrun (University of Southern California, USA)
Francois Faure (iMAGIS, University of Grenoble I, France)
Michael Gleicher (University of Wisconsin, USA)
Marcelo Kallmann (EPFL, Lausanne, Switzerland)
Ming Lin (University of North Carolina, USA)
Laurent Moccozet (University of Geneva, Switzerland)
Hong Qin (State University of New York, USA)
Hansrudi Noser (University of Zurich, Switzerland)
Werner Purgathofer (Technical University of Wi en, Austria)
Frank van Reeth (Limburgs University Center, Belgium)
Pascal Volino (University of Geneva, Switzerland)
Reviewers
Eric G. Aaron (University of Pennsylvania, USA)
Jan M. Allbeck (University of Pennsylvania, USA)
Koji Ashida (University of Pennsylvania, USA)
Kevin T. McDonnell (State University of New York, USA)
Olaf Etzmuss (University of Tuebingen, Germany)
Chris Faisstnauer (Technical University of Wien, Austria)
Jing Hua (State University of New York, USA)
Heinrich Hey (Technical University of Wi en, Austria)
Seung-Joo Lee (University of Pennsylvania, USA)
Jean-Sebastien Monzani (EPFL, Lausanne, Switzerland)
Yannick Remion (University of Reims, France)
Etienne de Sevin (EPFL, Lausanne, Switzerland)
Branislav Ulicny (EPFL, Lausanne, Switzerland)
Alexander Wilkie (Technical University of Wi en, Austria)
Michael Wimmer (Technical University of Wi en, Austria)
Jian Jun Zhang (Boumemouth University, UK)
Liwei Zhao (University of Pennsylvania, USA)
Contents
1. Motion Capture and Control
Markerless Motion Capture of Complex Full-Body Movement
for Character Animation ................................................................................................. .3
Andrew 1. Davison, Jonathan Deutscher and Ian D. Reid
Implementation of a 3D Virtual Drummer ......................................................... 15
Martijn Kragtwijk, Anton Nijholt and Job Zwiers
2. Deformations for Animation
Animating with the" Multidimensional deformation tool " ...................................... 29
Dominique Bechmann and Mehdi Elkouhen
Mixing Triangle Meshes and Implicit Surfaces in Character Animation..................... 37
Antoine Leclercq, Samir Akkouche and Eric Galin
3. Natural Phenomena
Visual Simulation of Smoke and Fire ............................................................... 51
Jos Stam
Phenomenological Simulation of Brooks .......................................................... 53
Fabrice Neyret and Nathalie Praizelin
An interactive forest ................................................................................... 65
Thomas Di Giacomo, Stephane Capo and Franr;ois Faure
Meshes on Fire ......................................................................................... 75
Haeyoung Lee, Laehyun Kim, Mark Meyer and Mathieu Desbrun
4. Physically-based Animation
Continuous deformation energy for Dynamic Material Splines
subject to finite displacements ....................................................................... 87
Olivier Nocent and Yannick Remion
x
Deformed Distance Fields for Simulation of Non-Penetrating
Flexible Bodies ................. , ...................................................................... 99
Susan Fisher and Ming C. Lin
Real-Time Simulation of Deformation and Fracture of Stiff
Materials .................................................................................... , ......... .113
Matthias Muller. Leonard McMillan. Julie Dorsey and Robert Jagnow
5. Hair Animation
A Simple Physics Model to Animate Human Hair Modeled in 2D
Strips in Real Time................................................................................. 127
Chuan Koon Koh and Zhiyong Huang
A Layered Wisp Model for Simulating Interactions inside
Long Hair ............................................................................................. .139
Eric Plante, Marie-Paule Cani and Pierre Poulin
6 . High Level Motion Planning
Efficient Multi-Agent Path Planning ............................................................... .151
Okan Arikan. Stephen Chenney and David A. Forsyth
Crowd simulation for interactive virtual environments and
VR training systems .................................................................................. 163
Branislav Ulicny and Daniel Thalmann
The Orchestration of Behaviours using Resources and
Priority Levels ...................................................................... '" ............... .171
Fabrice Lamarche and Stephane Donikian
Evolution and Cooperation of Virtual Entities with
Classifier Systems .................................................................................... 183
Cedric Sanza. Olivier Heguy and Yves Duthen
Appendix: Colour Illustrations ............................................................ 195
1
Motion Capture and Control
Markerless Motion Capture of Complex
Full-Body Movement for Character Animation
Andrew J. Davison, Jonathan Deutscher and Ian D. Reid
Robotics Research Group
Department of Engineering Science
University of Oxford
Oxford OX} 3PJ, UK
[ajd,jdeutsch,ian]@robots.ox.ac.uk
Abstract. Vision-based full-body tracking aims to reproduce the performance
of current commercial marker-based motion capture methods in a system which
can be run using conventional cameras and without the use of special apparel or
other equipment, improving usability in existing application domains and open
ing up new possibilities since the methods can be applied to image sequences
acquired from any source. We present results from a system able to perform
robust visual tracking with an articulated body model, using data from multiple
cameras. Our approach to searching through the high-dimensional model con
figuration space is an algorithm called annealed particle filtering which finds
the best fit to image data via multiple-layer propagation of a stochastic parti
cle set. This algorithm efficiently searches the configuration space without the
need for restrictive dynamical models, permitting tracking of agile, varied move
ment. The data acquired can readily be applied to the animation of CG char
acters. Movie files illustrating the results in this paper may be obtained from
http://www.robots.ox.ac.ukrajdIHMC/
1 Introduction
Motion capture aids animators in the time-consuming task of making computer graphics
characters move in realistic ways by enabling movement data to be recorded straight
forwardly from observation of an actor performing the desired motions. Commercial
human motion capture technology [16] has now been used for CG character animation
for a number of years. In typical current systems, a number of retro-reflective markers
are attached in known positions to the actor's body and viewed by infra-red cameras
emitting light and filtered to remove background signals. The easily-recovered image
positions of the markers are transformed into 3D trajectories via triangulation of the
measurements from multiple cameras, and a parameterised representation of the actor's
movements can be calculated.
It is a sign of the growing synergy between graphics and computer vision (seen
recently in areas such as augmented reality [15]) that visual processing can in fact be
used to recover motion data directly from images, without markers, and many analogues
can be seen in the processes used for tracking and those used later on to reanimate the
data in graphical output. The use of markers is intrusive and restricting, necessitates
the use of expensive specialised capture hardware, and requires footage to be taken
specially. The goal of markerless motion capture is to reproduce the performance of
marker-based methods in a system which could be run using conventional cameras and
without the use of special apparel or other equipment.
