1. Head Tracking and Action Recognition in a Smart Meeting Room
Hammadi Nait-Charif
& Stephen J. McKenna

2. Objectives Simultaneously track multiple people
Perform automatic initialization
Handle Person-Person Occlusion
Combine data from the 2 cameras to annotate the activity of all 6 participants

3. SIS Algorithm

4. SIS Algorithm Solutions to degeneracy problem
Good Choice of Important Density
sub-optimal solution =>
2. Resampling

5. SIR Algorithm

6. Drawbacks of SIR Algorithm
Particles with high weight a statistically selected many times which leads to the loss of diversity of the particles
Prior is not the optimal choice for the importance function because it does not take into account the latest observation
3. SIR tends to be less accurate with smaller sample sets

7. ILW Algorithm

8. How ILW is Better
Half of the particles migrate to the high likelihood regions (because they take into account the latest measurement) in the state-space while the other half are sampled from the prior
So even if the prior is poor the estimate is better due the use of the other half of the particles in the high likelihood regions

9. Figure 1

10. Figure 2

11. Figure 3

12. Figure 4

13. Figure 5

14. Figure 6

15. Figure 7

16. Figure 8