Lecture 3. Virtual Worlds : Representation,Creation and Simulation ( II ) 고려대학교 그래픽스 연구실

Contents Representation of Virtual Worlds Creation of virtual Worlds Simulation of Virtual Worlds Simulation of Virtual Agents

Creation of Virtual Worlds {geometry, physics, behavior} 1. 3D Modeling and Layouting 2. Vision-based Techniques 3. Algorithmic Creation 4. Multimedia and Virtual World Authorings

1. Three-D modeling Methods for modeling 3D object geometry graphics library tedious, requires skill CAD package issue: CAD file format --> VR system’s representation commercial 3D database issue: polygonal mesh --> parts/objects 3D digitizer issue: sparse set of 3D points --> polygonal mesh VR editor

2. Vision-based techniques Various ‘Shape-from-X’ techniques Passive methods stereo vision model-based vision multi-view analysis Active methods laser range finding structured lights

4. Virtual world authoring Multimedia authoring CD-Rom titles Web pages Animation authoring Game authoring Virtual world authoring

Virtual world authoring environment single authoring environment vs. a collection of tools 3D model builder audio source and editor device drivers / library runtime module simulation rendering application builder

Application builder similar in spirit to the many 3D GUI builder. some useful features built-in, extensible object type system and browser direct scene graph manipulation object property editor script language (interpreted, but compilerable) access to external codes importing a variety of CAD formats support for a wide variety of devices What can we learn from the 2D GUI builder?

Simulation of Virtual Worlds H-sensor perception cognition motion control H-effector P-effector P-sensor L-effector L-sensor sensing action Human Virtual environment avatar virtual agent object V-effector V-sensor

1. Kinematics Simulation (e.g., collision detection) 2. Dynamics Simulation (e.g., collision response) 3. Behavioral Simulation 4. Management of the Distributed Virtual Worlds

Simulation is problem-dependent. Common issue: “N-body problem” given n objects, it takes O(n(n-1)) computations. Approaches (1) Distributed processing (2) “Multi-modeling” or Dynamic LoD

Dynamics LoD Select a simulation model as the function of … example dynamic states of simulation distance to the user, viewing condition distance between objects, etc. example rigid body --> kinematics/dynamics simulation --> point-mass Automatic generation of dynamic models in multiple levels is still elusive.

Collision detection Introduction Basic Algorithm and Its Problems Categorizing of previous methods State of the Art

Simulation of Virtual Agents 1. Virtual Body 2. Motion Control Techniques 3. Generation of Facial Expression 4. Case Study: Existing Systems Improv Jack

1. Virtual Body Representations Geometric representations appearance (geometry) kinematics dynamics Geometric representations skeleton muscles skin hair

Example - Humanoid (Thalmann) 3 levels of detail (2,000 ~ 40,000 polys) skeleton - meta-ball - body contours - skin with polys 74 DOFs (body) + 30x2 DOFs (hand)

2. Motion Control Techniques Key-frame animation Inverse kinematics Forward dynamics Inverse dynamics Motion capture

3. Generation of Facial Expression Brief History 70’s Gouraud (1971) demonstrated shading technique using his wife’s head model Chernoff (1971) computer generated 2D face drawings Gillenson (1973) interactive system for 2D line drawn facial images Ekman (1977) developed FACS(Facial Action Coding System) Parke (1972 -1979) Ivan Surtherland’s CG course at Univ of Utah, M.S. thesis. developed 3D facial animation system

80’s and later Parke (1980) Platt (1981) Brennan (1982) Waters (1987) developed the 3D parameterized facial animation system Platt (1981) developed the physically based muscle controlled facial model Brennan (1982) 2D facial caricatures Waters (1987) developed the muscle model Terzopoulos (1990) developed the dynamic model using lattice network Wang (1994) developed the hierarchical layered spline model etc.

FACS What is FACS? Definition of some facial knowledge 46 AUs (Action Units) qualitative motion of skin which makes a unique facial action 6 primary emotional expressions happy, sad, surprise, fear, anger, disgust widely used for facial animation systems

Action Units (AU) Example of AUs

Modeling methods Libraries of expression and interpolation Parametric models using expression parameters Physically-based models using dynamic equation Anatomy-based models Integration of additional features texture map, hair modeling, etc.

Parametrized Model [Parke 80] Approach face model includes “parameter set” Basic operation procedural construction interpolation rotation/scaling position offset

Muscle Model [Waters 87] Approach Muscle not the exact simulation of skin, muscles, etc. mimic the primary biomechanical characteristics. Muscle can be grouped by orientation of muscle fibers linear / parallel Elliptical / circular Sheet / flat

Dynamic model [Terzopoulos 90] using lattice network (volume network) three layers : skin, fat, muscle(& bone)

Spline Model [Wang 94] Hierarchical layered spline modelling local area surface deformation Level 2 Level 1 Level 3 Level 4

4. Case Study: Existing Systems Humanoid (Thalmann) Improv (Perlin) Jack (Badler) Hierarchical Virtual Characters (Bruderlin)