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A diffusion approach for interactive image retrieval

Hassan Tabout 1 Youssef Chahir 2 Abderrahman Sbihi 3 
2 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
Abstract : We study in this paper the problem of using multiple-instance semi-supervised learning to solve image Relevance feedback problem. Many multiple-instance learning algorithms have been proposed to tackle this problem; most of them only have a global representation of images. In this paper, we present a semi-supervised version of multiple instance learning. By taking into account both the multiple-instance and the semi-supervised properties simultaneously. A novel graph-based diffusion algorithm is developed, in which global and local information are used. Experimental results show promising results of the proposed method for a test database containing more than 2000 color seaweed images.
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Hassan Tabout, Youssef Chahir, Abderrahman Sbihi. A diffusion approach for interactive image retrieval. Studia Informatica Universalis, Hermann, 2010, 8 (4), pp.111-127. ⟨hal-00808245⟩

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