short-paper

Multiple Measurements and Joint Dimensionality Reduction for Large Scale Image Search with Short Vectors

Authors:

Filip Radenović,

Ondrej ChumAuthors Info & Claims

ICMR '15: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval

Pages 587 - 590

https://doi.org/10.1145/2671188.2749366

Published: 22 June 2015 Publication History

Abstract

This paper addresses the construction of a short-vector (128D) image representation for large-scale image and particular object retrieval. In particular, the method of joint dimensionality reduction of multiple vocabularies is considered. We study a variety of vocabulary generation techniques: different k-means initializations, different descriptor transformations, different measurement regions for descriptor extraction. Our extensive evaluation shows that different combinations of vocabularies, each partitioning the descriptor space in a different yet complementary manner, results in a significant performance improvement, which exceeds the state-of-the-art.

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Cited By

Wei BJia RFu SLyu XGao LTang Z(2022)MIR: A Benchmark for Molecular Image Retrival with a Cross-modal Pretraining Framework2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM55620.2022.9995641(3902-3904)Online publication date: 6-Dec-2022
https://doi.org/10.1109/BIBM55620.2022.9995641
Krishna TMcGuinness KO'Connor NCheng WKankanhalli MWang MChu WLiu JWorring M(2021)Evaluating Contrastive Models for Instance-based Image RetrievalProceedings of the 2021 International Conference on Multimedia Retrieval10.1145/3460426.3463585(471-475)Online publication date: 24-Aug-2021
https://dl.acm.org/doi/10.1145/3460426.3463585
Mahmoud AKaramti HHadjouni M(2020)A hybrid late fusion-genetic algorithm approach for enhancing CBIR performanceMultimedia Tools and Applications10.1007/s11042-020-08825-679:27-28(20281-20298)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/s11042-020-08825-6
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Index Terms

Multiple Measurements and Joint Dimensionality Reduction for Large Scale Image Search with Short Vectors
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

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Published In

cover image ACM Conferences

ICMR '15: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval

June 2015

700 pages

ISBN:9781450332743

DOI:10.1145/2671188

General Chairs:
Alex Hauptmann
Carnegie Mellon University, USA
,
Chong-Wah Ngo
City University of Hong Kong, China
,
Xiangyang Xue
Fudan University, China
,
Program Chairs:
Yu-Gang Jiang
Fudan University, China
,
Cees Snoek
University of Amsterdam and Qualcomm Research Netherlands
,
Nuno Vasconcelos
University of California, San Diego, USA

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

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Published: 22 June 2015

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ICMR '15

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SIGMM

ICMR '15: International Conference on Multimedia Retrieval

June 23 - 26, 2015

Shanghai, China

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ICMR '15 Paper Acceptance Rate 48 of 127 submissions, 38%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Wei BJia RFu SLyu XGao LTang Z(2022)MIR: A Benchmark for Molecular Image Retrival with a Cross-modal Pretraining Framework2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM55620.2022.9995641(3902-3904)Online publication date: 6-Dec-2022
https://doi.org/10.1109/BIBM55620.2022.9995641
Krishna TMcGuinness KO'Connor NCheng WKankanhalli MWang MChu WLiu JWorring M(2021)Evaluating Contrastive Models for Instance-based Image RetrievalProceedings of the 2021 International Conference on Multimedia Retrieval10.1145/3460426.3463585(471-475)Online publication date: 24-Aug-2021
https://dl.acm.org/doi/10.1145/3460426.3463585
Mahmoud AKaramti HHadjouni M(2020)A hybrid late fusion-genetic algorithm approach for enhancing CBIR performanceMultimedia Tools and Applications10.1007/s11042-020-08825-679:27-28(20281-20298)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/s11042-020-08825-6
Fan LZhao HZhao HLiu PHu H(2019)Image Retrieval Based on Learning to Rank and Multiple LossISPRS International Journal of Geo-Information10.3390/ijgi80903938:9(393)Online publication date: 4-Sep-2019
https://doi.org/10.3390/ijgi8090393
Radenovic FTolias GChum O(2019)Fine-Tuning CNN Image Retrieval with No Human AnnotationIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2018.284656641:7(1655-1668)Online publication date: 1-Jul-2019
https://doi.org/10.1109/TPAMI.2018.2846566
Raza MQamar URaza MQamar U(2019)BackgroundUnderstanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications10.1007/978-981-32-9166-9_2(27-51)Online publication date: 24-Aug-2019
https://doi.org/10.1007/978-981-32-9166-9_2
Liu PMiao ZGuo HWang YAi N(2018)Adding spatial distribution clue to aggregated vector in image retrievalEURASIP Journal on Image and Video Processing10.1186/s13640-018-0247-02018:1Online publication date: 7-Feb-2018
https://doi.org/10.1186/s13640-018-0247-0
Zhang X(2018)Near-Duplicate Image Retrieval Based on Multiple Features2018 IEEE Visual Communications and Image Processing (VCIP)10.1109/VCIP.2018.8698664(1-4)Online publication date: Dec-2018
https://doi.org/10.1109/VCIP.2018.8698664
Zheng LYang YTian Q(2018)SIFT Meets CNN: A Decade Survey of Instance RetrievalIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2017.270974940:5(1224-1244)Online publication date: 1-May-2018
https://doi.org/10.1109/TPAMI.2017.2709749
Kolla MVenu Gopal T(2018)Region-Based Semantic Image Clustering Using Positive and Negative ExamplesICCCE 201810.1007/978-981-13-0212-1_75(741-749)Online publication date: 1-Sep-2018
https://doi.org/10.1007/978-981-13-0212-1_75
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