User-driven Nearest Neighbour Exploration of Image Archives

Luca Piras, Deiv Furcas, Giorgio Giacinto


Learning what a specific user is exactly looking for, during a session of image search and retrieval, is a problem that has been mainly approached with “classification” or “exploration” techniques. Classification techniques follow the assumption that the images in the archive are statically subdivided into classes. Exploration approaches, on the other hand, are more focused on following the varying needs of the user. It turns out that image retrieval techniques based on classification approaches, though often showing good performances, are not prone to adapt to different users’ goals. In this paper we propose a relevance feedback mechanism that drives the search into promising regions of the feature space according to the Nearest Neighbor paradigm. In particular, each image labelled as being relevant by the user, is used as a “seed” for an exploration of the space based on the Nearest Neighbors paradigm. Reported results show that this technique allows attaining higher recall and average precision performances than other state-of-the-art relevance feedback approaches.


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Paper Citation

in Harvard Style

Piras L., Furcas D. and Giacinto G. (2015). User-driven Nearest Neighbour Exploration of Image Archives . In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5, pages 181-189. DOI: 10.5220/0005183401810189

in Bibtex Style

author={Luca Piras and Deiv Furcas and Giorgio Giacinto},
title={User-driven Nearest Neighbour Exploration of Image Archives},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},

in EndNote Style

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - User-driven Nearest Neighbour Exploration of Image Archives
SN - 978-989-758-076-5
AU - Piras L.
AU - Furcas D.
AU - Giacinto G.
PY - 2015
SP - 181
EP - 189
DO - 10.5220/0005183401810189