Head Tracking and Action Recognition in a Smart Meeting

Room

Hammadi Nait-Charif

& Stephen J. McKenna

Objectives

1. Simultaneously track multiple people

2. Perform automatic initialization

3. Handle Person-Person Occlusion

4. Combine data from the 2 cameras to annotate the activity of all 6 participants

SIS Algorithm

SIS Algorithm

Solutions to degeneracy problem

1. Good Choice of Important Density

sub-optimal solution =>

2. Resampling

SIR Algorithm

Drawbacks of SIR Algorithm

1. Particles with high weight a statistically selected many times which leads to the loss of diversity of the particles

2. 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

ILW Algorithm

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

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