Image Processing Reference

In-Depth Information

This description of the scene is constructed incrementally. The update of the world

model is conducted throughout the analysis process. The information gathered is char-

acterized by a confidence measure that makes it possible to evaluate the membership

coefficient of an entity to a given concept. This parameter evolves over time and prop-

agates through the information structure using Bayesian networks. The networks were

constructed with the “Bayes Net Toolbox
3
”.

For a given support, its confidence depends on three sources of information:

- the samples that have contributed to constructing it;

- the additional information, if there is any, such as the presence of movement;

- the other supports that have induced its construction by focusing (the concept of

lineage).

The calculation of confidence associated with each support can be shown in the

form of a causality graph. It depends on several sub-networks (Figure 10.8).

smpl
N

smpl 1

measurements taken

from the image

parent

sup

mov

id

the movement

focusing strategy

Figure 10.8.
Description of the Bayesian network used for calculating the confidence

of a support. This confidence depends on the confidence obtained for each sample,

on focusing relations and on the movement

We are going to describe each one of these sub-networks in detail:

- for each sample (Spl1, . . . SplN) that belongs to the support, a statistical analysis

is conducted in order to calculate the measure of confidence for each attribute (Att1,

. . . AttN). The system calculates this measure of confidence as a gap between two

probability distributions originating from the measure and the model. These measures

3. www.cs.berkeley.edu/%7Emurphyk/Bayes/bnt.html.

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