1227181

Une architecture multi-agent pour la détection, la
reconnaissance et l’identification de cibles
Fabienne Ealet
To cite this version:
Fabienne Ealet. Une architecture multi-agent pour la détection, la reconnaissance et l’identification de
cibles. Mathématiques [math]. Université Joseph-Fourier - Grenoble I, 2001. Français. �tel-00004678�
HAL Id: tel-00004678
https://tel.archives-ouvertes.fr/tel-00004678
Submitted on 16 Feb 2004
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A chaque noeud du graphe, on associe
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C
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D
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des états
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des
noeuds parents :
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Le modèle
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0.8
0.7
0.6
Probabilité de
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0.5
0.4
0.3
0.2
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0
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0
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Modèle du monde
Zone de l’image
Objectif
Recherche les
échantillons
instant t
Images
− localisation
− intermédiaires
Base de connaissance
Calcule la confiance
Echantillons
méthode de
localisation
Confiance
méthode de
détection
Active les agents
détection
demande de
Agent Localisation
création d’agents
à l’administrateur
(Zone, Objectif)
utilisé par l’agent
généré par l’agent
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Modèle du monde
Zone de l’image
Objectif
instant t
Recherche les
Echantillons
supports
Images
− segmentation
Base de connaissance
Calcule la confiance
méthode de
détection
méthode de
focalisation
Supports
Confiance
Active les agents
− Focalisation
− Décision
Agent Détection
demande de
création d’agents
à l’administrateur
(Zone, Objectif)
utilisé par l’agent
généré par l’agent
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(a)
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le paramètre
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le nom de la
méthode
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la relation
spatiale
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Modèle du monde
Zone de l’image
Objectif
instant t
Recherche les
nouvelles zones
d’intérêt
Base de connaissance
Supports
Image de
focalisation
méthode de
focalisation
méthode de
localisation
Active les agents
localisation
(sur nouvelle zone et avec
un nouvel objectif)
demande de
création d’agents
à l’administrateur
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(Zone, Objectif)
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Modèle du monde
Zone de l’image
Objectif
Recherche les
supports
en mouvement
instant t
Images
− Mouvement
Base de connaissance
Supports
Calcule la confiance
Confiance
méthode de
détection de
mouvement
Active les agents
Décision
demande de
Agent Mouvement
création d’agents
à l’administrateur
(Zone, Objectif)
utilisé par l’agent
généré par l’agent
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CIBLE
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MOUVEMENT
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NON CIBLE
Poursuivre le recherche
B<(C O %% ! .&6 " # 0204 % $"
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Modèle du monde
Zone de l’image
Objectif
instant t
Base de connaissance
Calcul la confiance
Supports
Confiance
méthode de
localisation
méthode de
reconnaissance
Activation des agents
− Localisation
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Images
− segmentation
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Agent Décision
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création d’agents
à l’administrateur
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généré par l’agent
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Objectif Initial
Zone d’analyse
Route
Image
1 Agent Concept
activation de la boucle exploration spatiale
1 Agent Localisation
recherche les échantillons vérifiant
les critères de gris, d’homogénéité,
et de surface
Résultat : 9 échantillons trouvés
9 Agent Détection
Dès qu’un échantillon est trouvé
Un agent Détection est crée
9 Agent Décision
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6&0 & & & !.&6 " & 24% !"
-0" & >6 )<D< !/ &6 & ! 2 4 >< 4 !%&! & "& !. > "
4 véhicules présents
probabilite comprise entre 67 et 74%
probabilite comprise entre 63 et 66%
probabilite inferieure a 63
fausses alarmes
véhicules détectés
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6%& < & " &" 4& "0&' &
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F
& /%&/
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Premier agent dans l’image
Les premières lettres donnent le type d’agent :
C = Agent Concept
L = Agent Localisation
Dt = Agent Détection
Dc = Agent Décision
Dc_V
Dc_V
Dt_V
Dt_V
Dc_V
Dt_V
Dt_V
C_V
Dt_V
L_V
Dt_V
Dc_V
Dc_V
La dernière lettre spécifie l’objectif
V= VEHICULE
Dt_V
Dt_V
Dt_V
Dc_V
Dc_V
Donne la probabilité d’appartenance
d’un support au concept véhicule
Dc_V
Dc_V
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probabilite comprise entre 40 et 45%
probabilite comprise entre 55 et 65%
4 véhicules présents
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FOCALISATION : "SUR"
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probabilite comprise entre 67 et 74%
Véhicule non détecté
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OBJECTIF
ROUTE
Premier agent créé dans l’image
OBJECTIF
VEHICULE
C_R
Dt_R
L_R
Dt_R
Fs_R
Dt_V
Dc_V
Fs_R
Dt_R
L_V
L_V
Fs_R
Dc_V
Dt_V
Dt_V
Dc_V
L_V
DcV
Donne la probabilité d’appartenance
d’un support au concept véhicule
Les premières lettres donnent le type d’agent :
C = Agent Concept
L = Agent Localisation
Dt = Agent Détection
F= Agent Focalisation ( indexé par un type : s = sur)
Dc = Agent Décision
La dernière lettre spécifie l’objectif
V= VEHICULE
R= ROUTE
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<
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FOCALISATION : "SUR"
FOCALISATION : "A COTE DE"
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véhicule détecté
Probabilités d’appartenance au concept véhicule :
probabilite comprise entre 67 et 74%
probabilite inferieure a 63
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& /%&/
OBJECTIF
ROUTE
OBJECTIF
VEHICULE
Premier agent créé dans l’image
L_R
Dt_R
C_R
Fa_R
L_R
Fs_R
L_V
Dt_V
Dt_R
Fa_R
Dc_V
L_R
Fs_R
L_V
L_V
L_V
Dt_V
Dt_R
Dc_V
Dt_V
Fs_R
Dt_V
Fa_R
Dc_V
L_V
Dc_V
L_V
DcV
Donne la probabilité d’appartenance
d’un support au concept véhicule
Les premières lettres donnent le type d’agent :
C = Agent Concept
L = Agent Localisation
Dt = Agent Détection
F= Agent Focalisation ( indexé par un type : s = sur, a = à côté de)
Dc = Agent Décision
La dernière lettre spécifie l’objectif
V= VEHICULE
R= ROUTE
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Premier agent créé dans l’image
Les premières lettres donnent le type d’agent :
C = Agent Concept
L = Agent Localisation
L_V
Dt = Agent Détection
F = Agent Focalisation (index s=sur)
L_V
M = Agent Mouvement
Dc = Agent Décision
C_C
Dt_C
L_C
M_V
Dc_V
Fs_C
Dt_C
Dt_C
Fs_C
Fs_C
L_V
L_V
Dt_C
L_V
Fs_C
L_V
L_V
L_V
L_V
La dernière lettre spécifie l’objectif
C = CHAMP
V= VEHICULE
Dt_V
Dc_V
Exploration
Spatiale
Mouvement
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