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:
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.
COURSE READING MATERIALS
Reference Papers Used in Lectures:
ASSIGNMENTS AND PROJECTS
The class grade of each student is determined by
POINTERS TO WEBSITES ON PHYSICALLY-BASED MODELING & ANIMATION:
SELECTED INDUSTRY
SELECTED RESEARCH GROUPS:
SELECTED RESEARCHERS
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:
ADDITIONAL REFERENCE MATERIALS
Other Reference Books in Computer Animation:
Other Reference Books in Mechanics:
Other Reference Books in Numerical Methods:
Other Reference Books in Robotics:
Other Reference Books in Geometry:
For more information, contact
Ming C. Lin,
lin@umd.edu.
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