Global image representation using Locality-constrained Linear Coding for large-scale image retrieval

Yu Hsing Wu, Wei Lin Ku, Wen-Hsiao Peng, Hung Chun Chou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper proposes a global image representation based on Locality-constrained Linear Coding (LLC), with an aim to simplify the encoding process of local descriptors so as to facilitate large-scale image retrieval. Starting from the state-of-the-art Fisher Vector (FV) representation, we replace the computation of sophisticated posterior probabilities with simpler LLC. We then conduct several empirical studies to investigate the effects and benefits of this change and to adapt the other terms in FV for a better trade-off between performance and complexity. The result is a simpler global descriptor that combines the merits of both FV and LLC. Experimental results show that when compared with other similar works, our scheme not only brings performance benefits in mean Average Precision, but also offer complexity advantages.

Original languageEnglish
Title of host publication2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages766-769
Number of pages4
ISBN (Print)9781479934324
DOIs
StatePublished - 1 Jan 2014
Event2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014 - Melbourne, VIC, Australia
Duration: 1 Jun 20145 Jun 2014

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2014 IEEE International Symposium on Circuits and Systems, ISCAS 2014
CountryAustralia
CityMelbourne, VIC
Period1/06/145/06/14

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