Feedback-based Dynamically Weighted BoF for Image Retrieval

DOI

10.2991/icmemtc-16.2016.296How to use a DOI?

Keywords

Bag of Features; content-based image retrieval; dynamically weighting; post-query process

Abstract

Bag of Features (BoF) has been successfully exploited in content-based image retrieval for several years. Due to its performance and popularity, several extensions have been proposed that involve feature description, dictionary building, feature encoding and post-query process, etc. This paper proposes a dynamically weighting scheme for BoF-based image retrieval based on feedback. It involves two contributions: (i) analyzing the statistical distribution characteristic of similar BoF representations and (ii) computing weights dynamically based on the feedback obtained from different initial query results. We quantitatively evaluate the proposed method on two different databases. Experiments confirm that the proposed weighting scheme has better performance than the baseline of BoF-based image retrieval systems. Meanwhile, the results demonstrate the effectiveness of the weighting scheme in terms of the precision of top-N returned images.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanyan Gao
AU  - Yingqian Jia
AU  - Ning Li
AU  - Li Li
PY  - 2016/04
DA  - 2016/04
TI  - Feedback-based Dynamically Weighted BoF for Image Retrieval
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1539
EP  - 1545
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.296
DO  - 10.2991/icmemtc-16.2016.296
ID  - Gao2016/04
ER  -