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CS7496 Computer Animation
Instructor: C. Karen Liu
Karen Liu
Associate Professor at School of Interactive Computing
CS7496 Computer Animation Instructor: C. Karen Liu Karen Liu - - PowerPoint PPT Presentation
CS7496 Computer Animation Instructor: C. Karen Liu Karen Liu - - PowerPoint PPT Presentation
CS7496 Computer Animation Instructor: C. Karen Liu Karen Liu Associate Professor at School of Interactive Computing Karen Liu Associate Professor at School of Interactive Computing Our TA: Vivek Trivedi Administrations
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Karen Liu
Associate Professor at School of Interactive Computing
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Our TA: Vivek Trivedi
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Administrations
✦ http://www.cc.gatech.edu/classes/AY2014/cs7496_fall/ ✦ Course slides and projects are online. ✦ No textbook, but there will be online reading materials. ✦ Office hours: Tue 2-00-3:00, TSRB 230A. ✦ TA office hours:
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My goals
✦ To introduce basic techniques and math tools for simulation,
analysis, and control of dynamic systems.
✦ To teach you how to find and formulate your research problems. ✦ To inspire some of you to do research in computer graphics,
robotics, or biomechanics.
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You will learn how to…
✦ simulate particles, rigid bodies, articulated rigid bodies, deformable
- bjects, fluids, cloth.
✦ numerical integration of ODEs, rigid body dynamics, constrained
systems, collision detection and handling, Lagrangian dynamics, finite element methods, fluid mechanics.
✦ motion synthesis of locomotion, hand manipulation, facial
animation, skin/muscle deformation.
✦ optimization methods, optimal control theory, biped balance
control, manipulation control, reinforcement learning, skinning techniques, motion capture.
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You will not learn…
✦ how to use commercial animation tools such as Maya. ✦ how to use game engines such as Unity. ✦ how to render high quality animation.
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Prerequisites
✦ Thorough understanding of linear algebra. ✦ Vector calculus. ✦ Proficient in C++. ✦ No need to have background in graphics.
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Grading
✦ Reading assignments (15%) ✦ Four mini projects (60%) ✦ Final project (25%) ✦ Quiz (0%)*
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Reading assignments
✦ We will read ~10 research papers. ✦ Each paper will be presented by a group of 2-3 students. ✦ For each paper, everyone will write a short review before the
presentation.
✦ Send me your top 3 papers before next Monday. I’ll do the
matching and scheduling. First come first serve!
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Projects
✦ Project 1: Particles. ✦ Project 2: Rigid body blender. ✦ Project 3: Fun with fluid. ✦ Project 4: Twister. ✦ Final project: Something about control. ✦ Late policy: 25% reduction per day if you don’t have a good reason. ✦ Everything has to be turned in before 12 pm on the due date.
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Final Project
✦ Something about control. ✦ Balance. ✦ Free throw. ✦ The elevator. ✦ Work with one partner on the final project.
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Quiz
✦ Quiz will be given and discussed in class from time to time. ✦ For every topic, expect 2-4 problems.
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Introduction
✦ Simulate dynamic systems. ✦ Control dynamic systems.
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Physics simulation
✦ An algorithm that produces a sequence of states over time under
the laws of physics.
✦ What is a state?
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Simulation
xi ∆x xi+1 xi+1 = xi + ∆x xi
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Simulation
xi ∆x xi+1 xi+1 = xi + ∆x xi
Newtonian laws gravity wind gust elastic force… integrator
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Ordinary differential equations
˙ x(t) = f(x(t))
known function time derivative of the unknown function unknown function that evaluates the state given time
F = ma An ODE is an equation involving a function and its derivatives.
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Quiz
✦ What function does the black box represent?
x ˙ x f
1. 2. 3.
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Solving ODE
✦ Standard introductory differential equation courses focus on
finding solutions analytically.
✦ Linear ODEs can be solved by integral transforms. ✦ We will learn how to solve an ODE numerically in this class.
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Rigid bodies
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Rigid bodies
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Articulated rigid bodies
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Deformable bodies
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Deformable bodies
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Plastic materials
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Fluids
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Fluids
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Fluids
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Fluids
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Cloth
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Cloth
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Fluids + Solids
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Fluids + Cloth
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Melted
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Drowned
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Immolated
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Waterboarded
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Skewered
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Crushed
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Mutilated
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Introduction
✦ Simulate dynamic systems. ✦ Control dynamic systems.
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Control rigid bodies
Popovic et al, 2001
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Control rigid bodies
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Control rigid bodies
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Control fluids
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Control fluids
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Control virtual humans
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Why is this hard?
✦ Human musculoskeletal system has a large number of degrees of
freedom and nonlinear dynamics
✦ The control mechanism must be robust to operate in complex
world.
✦ No qualitative ways to measure “Naturalness”
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Human motion
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Without control
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Why is this hard?
✦ Human musculoskeletal system has a large number of degrees of
freedom and nonlinear dynamics
✦ The control mechanism must be robust to operate in complex
world.
✦ No qualitative ways to measure “Naturalness”
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Complex animals movements
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Simulation
xi ∆x xi+1 xi+1 = xi + ∆x xi
Newtonian laws gravity wind gust elastic force… integrator
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Simulation
xi ∆x xi+1
Newtonian laws gravity wind gust elastic force… integrator
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Simulation + Control
xi ∆x xi+1
Newtonian laws integrator gravity contact force muscle force…
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Physics approach
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Physics approach
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Physics approach
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Why is this hard?
✦ Human musculoskeletal system has a large number of degrees of
freedom and nonlinear dynamics
✦ The control mechanism must be robust to operate in complex
world.
✦ No qualitative ways to measure “Naturalness”
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Data-driven approach
✦ Use captured data to synthesize
and interpolate new motions.
✦ Preserve detailed nuances of
human movements in the real world.
✦ Produce stable and compelling
animations in real-time.
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Motion capture
✦ Many different approaches. Our lab has an
- ptical based system.
✦ Multiple infrared cameras. ✦ High temporal resolution (1000+ fps). ✦ Detect the locations of reflective markers.
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Raw data from mocap
✦ Capture 3D positions of the markers. ✦ Require inverse kinematics post-processing to produce animation
represented as joint angle trajectories.
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Final motion
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Skinning
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