1. Data Driven Models of Motion Walking the Fine Line Between Performance, Realism and Style Chris White G-Lunch 2007

2. A Motivating Thought Experiment You are the lead developer on an upcoming video game. The designer gives you the following requirements: –This game must have tons of fire –Nobody will buy the game if the fire does not look real What do you do?

3. Uncanny Valley

4. Roadmap Video Textures Motion Graphs Synthesizing Motion from Annotations Group Motion Graphs

5. Video Textures

6. Markov Property of Video Frame i Frame j Frame k Frame l Frame m P(i,k) P(i,j) P(k,m)

7. Probability of a Transition Frames i, j

8. Is Video really Markovian? Alternative Question: Why is C0 continuity not enough?

9. Dead End Transitions

10. Interesting Open Problems Relighting?

11. Motion Graphs Apply Video Textures idea to motion capture data

12. Motion Graph Clip i Clip j Clip k Clip l Clip m P(i,k) P(i,j) P(k,m)

13. Detecting Candidate Transitions Weighted sum of L2 distance of point clouds of joint positions

14. Candidate Transitions Continued Find local minima of optimization

15. Bad Transitions Sinks and Dead Ends Compute Strongly Connected Components

16. Searching for motion Random graph walk is only useful as an elaborate screen saver User supplies function g(w,e) describing additional error of adding edge e to path w Total error of path is:

17. Downside Designers/artists do not like specifying their desires as mathematical functions

18. Motion Synthesis from Annotations Allow animator to paint semantically meaningful timeline for motion

19. Annotating the Motion Database Generate meaningful vocabulary –For football: Run, Walk, Wave, Jump, Turn Left, Turn Right, Catch, Reach, Carry, Crouch, Stand, Pick up For each term, designer annotates small subset of database Support Vector Machine classifies remaining motions

20. Generating Motion Minimize the objective function: D(i,A(f)) determines if annotation is met at that frame C measures the continuity of putting two frames together

21. Optimize using Dynamic Programming

22. Interesting Extensions Explore the space of motions –We looked at the space of BRDFs last semester