1. 1cs426-winter-2008 Notes  Assignment 1 is out, due immediately after reading week (Feb 25)  Please read: William T. Reeves, "Particle systems: a technique for modelling a class of fuzzy objects", SIGGRAPH 1983 Gavin Miller and Andrew Pearce, "Globular dynamics: a connected particle system for animating viscous fluids", SIGGRAPH 1989

2. 2cs426-winter-2008 Match move  Matching up CG camera to real-footage  Easy version: Have rough CG model corresponding to real scene already, just solving for camera  Hard version: Need to figure out CG model as well

3. 3cs426-winter-2008 Match points  Need to identify image space positions of enough world space points in each frame Technically only need 3 non-collinear if field- of-view is known, 4 if not More points are essential for robustness  Also deal with camera distortions  Typically identify points by hand For difficult scenes (grass?) may need computer vision techniques, or just put stuff in the scene to track (and paint over later)

4. 4cs426-winter-2008 Solving match move  This essentially boils down to the same problem as IK, though numerically harder Ask the computer to find camera parameters which give as good a fit for all the match points as possible Since some match points may be misidentified, need to robustly deal with outliers (discard suspicious data)  May need interactive help from user to lock on (first guess at camera parameters etc.)  It helps a lot if real-life measurements made to determine exactly where match points are in world-space But if not, can still reconstruct it from the data…

5. 5cs426-winter-2008 3D reconstruction  Leads into another hot topic: 3D model reconstruction  Active scanning: stick object (or person) in 3D scanner Can get very high accuracy  Passive reconstruction: try to build a good CG model from footage (or extra photos) itself Much harder, much more useful, slow progress being made

6. 6cs426-winter-2008 Procedural Animation

7. 7cs426-winter-2008 Particle Systems  For fuzzily defined phenomena, highly complex motion, etc. particle systems provide a (semi-)automatic means of control  Break up complex phenomena into many (hundreds, thousands, or more) component parts E.g. fire into tiny flames  Instead of animating each part by hand, provide rules and overall guidance for computer to construct animation

8. 8cs426-winter-2008 When in doubt…  Used to model particle-like stuff: dust, sparks, fireworks, leaves, flocks, water spray…  Also phenomena with many DOF: fluids (water, mud, smoke, …), fire, explosions, hair, fur, grass, clothing, …  Three things to consider: When and where particles start/end The rules that govern motion (and additional attached variables, e.g. colour) How to render the particles

9. 9cs426-winter-2008 What is a particle?  Most basic particle only has a position x  Usually add other attributes, such as: Age Colour Radius Orientation Velocity v Mass m Temperature Type  The sky is the limit - e.g. AI models of agent behaviour