Content-based image retrieval (CBIR) has been
under investigation for a long time, with many systems
built to meet different application demands. However, in all
systems there is still a gap between user expectations and
system retrieval capabilities. Therefore, user interaction is
an essential component of any CBIR system. Interaction
up to now has mostly focused on changing global image
features or similarities between images. We consider the
interaction with salient details in an image, i.e., points, lines,
and regions. Interactive salient detail definition goes further
than summarizing the image into a set of salient details. We
aim to dynamically update the user- and context-dependent
definition of saliency based on relevance feedback. To
that end, we propose an interaction framework for salient
details from the perspective of the user. A number of
instantiations of the framework are presented. Finally, we
apply our approach for query refinement in a detail-based
image retrieval system with salient points and regions.
Experimental results prove the effectiveness of adapting the
saliency from user feedback in the retrieval process.
@InProceedings{NguyenSMS2005,
author = "Nguyen, G. P. and Worring, M.",
title = "Relevance Feedback Based Saliency Adaptation in CBIR",
booktitle = "ACM Springer Multimedia Systems",
number = "6",
volume = "10",
pages = "499--512",
year = "2005",
url = "https://ivi.fnwi.uva.nl/isis/publications/2005/NguyenSMS2005"
}