Performances of mobile-agents for interactive image retrieval
Résumé
In this paper, we present a system for image retrieval over a network of computer based on “ant-like” mobile- agents. Image databases are hosted on the network, and the user wants to find all the images matching a specific con- cept (cars, flower, Italy, etc...). Usually, content based im- age retrieval systems (CBIR) do not consider the dispertion of the data among the network. We train a SVM classifier with examples annotated by the user and then launch mobile agents which explore the network in order to retrieve the most relevant images. Several interactive session (launch- ing of agents then annotation of the results) are made to improve the classifier. Experiments are made both to see the influence of local- ization of the search concept on the quality of the learning, and to focus on the quality of the agent based solution com- pared to a centralizing system within a fixed amount of time for the interaction.