Department of Computer Science
College of Computer, Mathematical, and Natural Sciences
The University of Maryland at College Park
CMSC 828X (Fall 2022): Learning-based Modeling, Simulation and Animation
CMSC 828X (Fall 2022): Learning-based Modeling, Simulation and Animation
- Time and Place: Tues/Thur 12:30pm - 1:45pm, CSIC 2120
- Office Hours: Tues/Thur After Class
- Prerequisites: Scientific Computing AND
Introductory Computer Graphics (Optional) OR
Instructor's approval
- Textbook: Course Notes and In-Class Handouts
COURSE OVERVIEW:
Physically-based modeling and simulation attempts to map a natural
phenomena to a computer simulation program. There are two basic processes
in this mapping: mathematical modeling and
numerical solution. The goal of
this introductory course is to understand both of them. The mathematical
modeling
concerns the description of natural phenomena by
mathematical equations. Differential equations that govern dynamics
and geometric representation of objects are typical
ingredients of the mathematical model.
The numerical solution involves computing an efficient and accurate
solution of the mathematical equations. Finite precision of numbers,
limited computational power and memory forces us to approximate the
mathematical model with simple procedures.
In the first part of this course, we will study various techniques
to simulate the physical and mechanical behavior of objects in a
graphical simulation or a virtual environment. Students will learn
about implementation of basic simulation programs that produce
interesting results and verify its correctness. The course will
cover three basic components in physically-based modeling and
simulation:
In the second part of the course, we'll study most recent advances on learning-based algorithms, built on the state-of-the-art physics-based modeling, simulations, and animation data to learn the dynamics and motion of moving objects and characters.
The goal of this class is to get students an appreciation of
computational methods for modeling of motions in the physical and
virtual world through BOTH model-based and DATA-DRIVEN methods.
We will discuss various considerations and tradeoffs
used in designing simulation methodologies (e.g. time, space, robustness,
and generality). This will include network models and architectures, data structures, algorithms, computational methods and learning-based motion
reconstruction techniques, their complexity and implementation.
The lectures will also cover some applications of
physics vs. learning-based modeling and simulation to the following areas:
Computer Animation
Virtual Environments
Medical Simulation and Analysis
Special Effects Generation
Computer Game Dynamics
Rapid Prototyping for Design
Haptic Rendering/Interfaces
Robotics and Automation
Bio-informatics
Depending on the interests of the students, we may also cover
geometric-based simulation techniques, such as constraint-based
systems, optimization-based animation, inverse dynamics,
kinematics of motions, motion planning and synethesis of autonomous agents.
LECTURES AND APPROXIMATE SCHEDULE
Here is a list of TENTATIVE lecture topics (subject to
changes). Schedule and information on each topic (e.g. readings, web
pointers) will be added during the semester before each class.
Overview (Tues, Aug 30, 2022)
Basics of Motion Generations for Animation
(Thur, Sept 1, 2022)
Principles of Animation and Inverse Kinematics
(Tues, Sept 6, 2022) with Supplementary Video
ODE Basics: Initial Value Problem &
(Thur, Sept 8, 2022)
No Class (Tues, Sept 13, 2022) - Sub Live Demo Sesssion on Sept. 22
Intro to Particle Dynamics &
Particle Systems
(Thur, Sept 15, 2022)
Implicit Methods &
Particle LODs &
Solutions to Spring-Mass System
(Tues, Sept 20, 2022)
Constrained Dynamics
(Thur, Sept. 22, 2022)
Homework #1 Live Demo @ IRB 5107 (4:45pm-5:45pm) (Thur, Sept. 22, 2022)
Review on Comp Geom
(Tues, Sept 27, 2022)
Review on Comp Geom &
Collision Detection: Convex Polyhedra & Many Bodies
(Thur, Sept 29, 2022)
Collision Detection: Convex Polyhedra & Many Bodies
- Makeup Lecture posted on ELMS
(Tues, Oct 4, 2022)
Collision Detection: BVHs & Spatial Partitioning
- Makeup Lecture posted on ELMS
(Tues/Thur, Oct 4-6, 2022)
Project Proposal Presentations
(Tues/Thur, Oct 11-13, 2022)
Rigid Body Dynamics
(Notes on Quaternion,
Particle to Rigid Body Dynamics, and
More)
(Tues, Oct 18, 2022)
Modeling of Deformable Models: Introduction
(Thur, Oct 20, 2022)
Machine Learning for Virtual Try-On
(Tues, Oct 25, 2022)
Differentiable Physics: Rigid, Articulated, Deformable & Cloth Simulation
(Thurs, Oct 27, 2022)
Recent Advances in Deformable Models
and Hyperelastic Material Models
(Tues, Nov 1, 2022)
Introduction to Fluid Simulation
and Differentiable Fluid Dynamics
(Thur, Nov 3, 2022)
Voronoi Diagrams and Applications in Motion Planning
(Tues, Nov 8, 2022)
Embodied AI and Indoor Navigation Simulators
(Tues, Nov 8, 2022)
Interactive Household Environment Simulator for Embodied AI
(Nov 10, 2022)
Digital Humans
(Nov 10, 2022)
Midterm Project Proress Report
(Nov 15-17, 2022)
Learning-based Simulation and Animation Using GNNs
(Nov 17, 2022)
Crowd & Traffic Simulations
(Nov 22, 2022)
THANKSGIVING BREAK (Nov 23-25, 2022)
Reinforcement Learning for Dynamics Simulation
(Nov 17/29, 2022)
Hybrid Contact Modeling for Contact-rich Robot Manipulation
(Nov 29, 2022)
Motion Retargeting
(Dec 1, 2022)
N-body and Hydrodynamic Simulations in Astrophysics
(Dec 1, 2022)
AI in Real-time Interactive Simulations for Video Games
(Dec 6, 2022)
Traffic Modeling & Simulation
(Dec 6, 2022)
Brain-Computer Interfaces
(Dec 8, 2022)
Modeling Emotions Using EEG Signals (I)
(Dec 8, 2022)
COURSE READING MATERIALS
Reference Papers Used in Lectures:
SIGGRAPH
Course Notes on Physically-Based Modeling
Supplementary Materials and
Reading List for the Class
(updated throughout the semester)
Additional Notes on Rigid Body Dynamics:
Constraint-based Dynamics,
and Impulse-based Dynamics
ASSIGNMENTS AND PROJECTS
The class grade of each student is determined by
Homework (30%)
Class Presentation (20%)
Final Project (50%)
POINTERS TO WEBSITES ON PHYSICALLY-BASED MODELING & ANIMATION:
SELECTED INDUSTRY
Boston Dynamics Inc.
Chris Hecker's Corner (Definition Six, Inc.)
Dreamworks Animation
GamaNetwork
Havok
IBM Smarter Planet
Immersion Corporation
Legion Limited
Massive Software
MAYA
(Alias|Wavefront)
MSC.Working Knowledge
NVIDIA PHYSX
Pixar Animation Studios
Rhythm & Hues Studios
SensAble Technology
Walt Disney Animation Studio
Weta Digital
SELECTED RESEARCH GROUPS:
UNC Research Group
on Geometric Algorithms for Modeling, Motion and Animation
UNC Interactive
Collision Detection and Proximity Queries Packages
Simlab:
Computer Tools for Analysis and Simulation (Cornell)
iMAGIS
(GRAVIR / IMAG research lab / INRIA)
Center for Human Modeling and
Simulation(UPENN)
MIRALab (University of Geneva)
Rutgers Computational Biomedicine
Imaging and Modeling (Rutgers)
National Advanced Driving Simulator
University
of Aukland, Bioengineering Research Group
SELECTED RESEARCHERS
Norman Badler
David Baraff (now at Pixar)
Ronan Boulic
David Breen
Chris Bregler
Robert Bridson
Marie-Paule Cani
Stephen Chenney
Mathieu Desbrun
Petros Faloutsos
Ron Fedkiw
Eugene Fiume
Doug James
Jessica Hodgins
Michael Gleicher
Hyeong-Seok Ko
Dimitris Metaxas
Brian
Mirtich (now at Cognex)
James O'Brien
Carol O'Sullivan
Richard Parent
Dinesh Pai
Nancy Pollard
Jovan Popovic
Zoran Popovic
Jos Stam
Peter Schroder
Karan Singh
Daniel Thalmann
Nadia Magnenat-Thalmann
Demetri Terzopoulos
Yizhou Yu
Michiel van de Panne
Andy
Witkin's Gallery (now at Pixar)
GEOMETRIC ALGORITHMS AND SOFTWARES AVAILABLE ON THE WEB:
Here are just some possible locations to find geometric software/libraries
and algorithmic toolkits you may need:
Internet
Finite Element Resources
A comprehensive
collection of geometric software
CGAL: Computational
Geometry Algorithms Library (in C++)
LEDA:
Library of Efficient Datatypes and Algorithms (in C++)
The Stony
Brook Algorithm Repository: Implementation in C, C++, Pascal and Fortran
CMU's Computer Vision Homepage
Finite element
mesh generation and
More
Machine learning resources
ADDITIONAL REFERENCE MATERIALS
Other Reference Books in Computer Animation:
Making Them Move: Mechanics, Control and Animation of Articulated
Figures, by Badler, Barsky and Zelter, Morgan Kaufmann Publishers, 1991.
Advanced Animation and Rendering Techniques: Theory and Practice,
by A. Watt and M. Watt, 1992.
Computer Animation: Algorithms and Techniques, by Rick Parent, 1999.
Other Reference Books in Mechanics:
Concepts and Applications of Finite Element Analysis,
by R. D. Cook, D. S. Malkus and M. E. Plesha, John Wiley & Sons, 1989.
Finite Element Procedures, by K.-J. Bathe, Prentice Hall, 1996.
First Course in Continuum Mechanics, by Y.C. Fung,
Prentice Hall, 1993.
Other Reference Books in Numerical Methods:
Numerical Recipes,
by Press, Flanner, Teukolsky and Vetterling, Cambridge University Press.
Handbook
of Numerical Analysis, edited by Ciarlet and Lions, Vol. I - VI,
North-Holland, 1994.
Other Reference Books in Robotics:
Robot Motion Planning, by Latombe,
Kluwer Academic Publishers, 1991.
Planning Algorithms, by LaValle,
Cambridge University Press, 2006.
Robot Manipulators: Mathematics, Programming, and Control,
by R. P. Paul, MIT Press, 1981.
Other Reference Books in Geometry:
Computational Geometry (Algorithms and Applications), by de Berg,
van Kreveld, Overmars and Schwarzkofp, Springer-Verlag, 1997.
Computational Geometry In C (Second Edition), by
O'Rourke, Cambridge University Press, 1998.
Handbook on Discrete and Computational Geometry, by Goodman and
O'Rourke (eds), CRC Press LLC, 1997.
Applied Computational Geometry: Toward Geometric Engineering,
by Lin and Manocha (eds), Springer-Verlag, 1996.
Algorithms in Combinatorial Geometry, by Edelsbrunner,
Springer-Verlag, 1987.
Computational Geometry (An Introduction), by Preparata and Shamos,
Springer-Verlag, 1985.
For more information, contact
Ming C. Lin,
lin@umd.edu.
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