1. Real-time crowd motion planning: Scalable Avoidance and Group Behavior (2008) Authors: Yersin, Maïm, Morini, Thalman Presented by: Jessica Siewert

2. Content of presentation The Method: – Previous work – The architecture – Implementation – Experiments – Developments since Assessment

3. Introduction – Previous work Agent-based (low performance) Behavioral model (no high level control) Navigation graph (no inter-pedestrian collision avoid.) Various other approaches (no indiv. characteristics) Hybrid approaches

4. Introduction – Now we get… Improved hybrid architecture Realistic motion paths (planning) Realistic short term avoidance Small group behaviors

5. Introduction – Our method… Hybrid: – potential field – Navigation graph – New agent-based short term collision avoidance Three regions of interest – architecture Smooth transition between ROI’s

6. The architecture – Overview ROI 2: – Outside of view: no interest – Path planning by navigation graph – No collision handling ROI 1: – Visible in view: low interest – Path planning by navigation graph – Collision avoidance by potential field ROI 0: – Right in front of the camera – Path planning and collision avoidance by potential field

7. Implementation Initialization Classification Potential field computation Improved short-term avoidance algorithm Steering Continuity maintanance

8. Initialization & classification Active vertices Grid composing Elimination of cells Linkage to neighbors ROI 0, 1 and 2 lists

9. Potential field computation Goals Subgoals Sets/groups Waypoints Only in ROI 0/just outside ROI 0

10. Short-term avoidance Maximize speed, then minimize detours “Potential field failure” Identification of cells Security check Emergency avoidance

11. Steering & continuity Reynolds’ seek behavior (ROI 0 and 1) Linear steering in ROI 2 We use potential field for all coll. Av. Always update graph of ROI 1, even in ROI 0 Test graph path when exiting ROI 0

12. Group behavior 2-5 characters Speed adaptation Waypoint modification

13. Experiments

14. Experiments – Claim recall Improved hybrid architecture Realistic motion paths (planning) Realistic short term avoidance Small group behaviors Smooth transition between ROI’s

15. Movies… http://www.youtube.com/watch?v=QpwbhNE6Fe8 http://www.youtube.com/watch?v=ifimWFs5-hc

16. Developments since then http://portal.acm.org/citation.cfm?id=1410252

17. Assessment Circle approach Ermergency avoidance changes everything Skipping grid cells Size of the cells Fast pedestrians?

18. Assessment Decomposition methods/robustness? Crowd behavior – more decoupled sets Threshold experimentation Speeding up/slowing down relations De-linkage out of view

19. Assessment Frame rate Runtime Sets/groups definitions User opinions Not that many characters as they promised