Abstract
This paper presents a new and original model for image browsing and retrieval based on a reactive multi-agent system oriented toward visualization and user interaction. Each agent represents an image. This model simplifies the problem of mapping a high-dimensional feature space onto a 2D screen interface and allows intuitive user interaction. Within a unify and local model, as opposed to global traditional CBIR, we present how agents can interact through an attraction/repulsion model. These forces are computed based on the visual and textual similarities between an agent and its neighbors. This unique model allows to do several tasks, like image browsing and retrieval, single/multiple querying, performing relevance feedback with positive/nagative examples, all with heteregeneous data (image visual content and text keywords). Specific adjustments are proposed to allow this model to work with large image databases. Preliminary results on two image databases show the feasability of this model compared with traditional CBIR.
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Hong, H.C., Chiron, G., Boucher, A. (2013). A Multi-agent Model for Image Browsing and Retrieval. In: Nguyen, N., Trawiński, B., Katarzyniak, R., Jo, GS. (eds) Advanced Methods for Computational Collective Intelligence. Studies in Computational Intelligence, vol 457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34300-1_11
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DOI: https://doi.org/10.1007/978-3-642-34300-1_11
Publisher Name: Springer, Berlin, Heidelberg
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