1. Fast Synthetic Vision, Memory, and Learning Models for Virtual Humans

2. Purpose n Model synthetic vision, memory, and learning n Quickly synthesize motion from goals

3. Introduction n Virtual robot n Combines path planner and controller n Internal record of perceived objects and states

4. Related Work n Virtual perception n Model information flow to character

5. Synthetic Vision n Determine what is currently visible to character n Speed & ability to handle dynamic environments

6. Synthetic Vision - cont. n Render unlit model of scene from character’s POV n List of visible objects combined with each object’s location determines observations

7. A character in a virtual office True color False Color

8. Internal Representation & Memory n Internal model n Object geometry from environment and observed states

9. Perception-Based Navigation n Character has set M of observations n Observations represented as (objID i, P i, T i, v i, t) n M updated at regular intervals

10. Basic sense-plan-control loop (static environments)

11. Perception-Based Navigation - cont. n Dynamic environments

12. Perception-Based Navigation - cont. n Problem: Truly missing vs. obscured n Solution: Re-run vision module

13. Revised sense-plan-control loop (dynamic environments)

14. Learning and Forgetting n Temporal models n Different memory rules for different objects (logical or deductive model)

15. Experimental Results n Tested on SGI InfiniteReality2 n Click and drag goals and obstacles

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17. A character exploring unknown mazes

18. Conclusions n Efficient in storage and update times n Flexible n Bottlenecks at synthetic vision model (double rendering)