Abstract
Relevance feedback (RF) and region-based image retrieval (RBIR) are two widely used methods to enhance the performance of content-based image retrieval (CBIR) systems. In this paper, these two methods are combined. And a region weighting scheme reflecting the process of human visual perception is also proposed to enhance the weighting importance assigned to the region whose pixels are closer to the attention center. Furthermore, rather than using a single positive feedback group, the proposed approach introduces RBIR to the relevance feedback with multiple positive and negative groups. To guide users in grouping the positive feedbacks, the proposed system provides a heuristic pre-clustering result automatically. Using these guiding clusters, the users can re-group the positive feedbacks to express his/her particular interests. Finally, Group Biased Discriminant Analysis (GBDA) is modified and applied to the similarity measure between images constructed on the basis of the region-based relevance feedbacks.
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Su, WT., Chu, WS., Lien, JJ.J. (2006). Heuristic Pre-clustering Relevance Feedback in Region-Based Image Retrieval. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612704_30
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DOI: https://doi.org/10.1007/11612704_30
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