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research-article

Bundle min-hashing for logo recognition

Authors:

Stefan Romberg,

Rainer LienhartAuthors Info & Claims

ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval

Pages 113 - 120

https://doi.org/10.1145/2461466.2461486

Published: 16 April 2013 Publication History

Abstract

We present a scalable logo recognition technique based on feature bundling. Individual local features are aggregated with features from their spatial neighborhood into bundles. These bundles carry more information about the image content than single visual words. The recognition of logos in novel images is then performed by querying a database of reference images.

We further propose a novel WGC-constrained RANSAC and a technique that boosts recall for object retrieval by synthesizing images from original query or reference images. We demonstrate the benefits of these techniques for both small object retrieval and logo recognition. Our logo recognition system clearly outperforms the current state-of-the-art with a recall of 83% at a precision of 99%.

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Cited By

Chen YRuan XJain RChen YRuan XJain R(2024)Introduction to Logo DetectionRecent Advances in Logo Detection Using Machine Learning Paradigms10.1007/978-3-031-59811-1_2(33-41)Online publication date: 31-May-2024
https://doi.org/10.1007/978-3-031-59811-1_2
Mao KJin RChen KMao JDai G(2023)Trinity‐Yolo: High‐precision logo detection in the real worldIET Image Processing10.1049/ipr2.1279117:7(2272-2283)Online publication date: 30-Mar-2023
https://doi.org/10.1049/ipr2.12791
Tian NLiu YSun Z(2022)JN-Logo: A Logo Database for Aesthetic Visual AnalysisElectronics10.3390/electronics1119324811:19(3248)Online publication date: 9-Oct-2022
https://doi.org/10.3390/electronics11193248
Show More Cited By

Index Terms

Bundle min-hashing for logo recognition
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
2. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

cover image ACM Conferences

ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval

April 2013

362 pages

ISBN:9781450320337

DOI:10.1145/2461466

General Chairs:
Ramesh Jain
University of California, Irvine, USA
,
Balakrisknan Prabhakaran
University of Texas at Dallas, USA
,
Program Chairs:
Marcel Worring
University of Amsterdam, The Netherlands
,
John Smith
IBM Research, New York, USA
,
Tat-Seng Chua
National University of Singapore

Copyright © 2013 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]

Sponsors

SIGMM: ACM Special Interest Group on Multimedia

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2013

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ICMR'13

Sponsor:

SIGMM

ICMR'13: International Conference on Multimedia Retrieval

April 16 - 20, 2013

Texas, Dallas, USA

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ICMR '13 Paper Acceptance Rate 38 of 96 submissions, 40%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Chen YRuan XJain RChen YRuan XJain R(2024)Introduction to Logo DetectionRecent Advances in Logo Detection Using Machine Learning Paradigms10.1007/978-3-031-59811-1_2(33-41)Online publication date: 31-May-2024
https://doi.org/10.1007/978-3-031-59811-1_2
Mao KJin RChen KMao JDai G(2023)Trinity‐Yolo: High‐precision logo detection in the real worldIET Image Processing10.1049/ipr2.1279117:7(2272-2283)Online publication date: 30-Mar-2023
https://doi.org/10.1049/ipr2.12791
Tian NLiu YSun Z(2022)JN-Logo: A Logo Database for Aesthetic Visual AnalysisElectronics10.3390/electronics1119324811:19(3248)Online publication date: 9-Oct-2022
https://doi.org/10.3390/electronics11193248
Sharma NPenamakuri AMishra A(2022)Contrastive Multi-View Textual-Visual Encoding: Towards One Hundred Thousand-Scale One-Shot Logo Identification✱Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing10.1145/3571600.3571625(1-9)Online publication date: 8-Dec-2022
https://dl.acm.org/doi/10.1145/3571600.3571625
Fan XZhang CYang YShang YZhang XHe ZXiao YLong BWu LZhang ARangwala H(2022)Automatic Generation of Product-Image Sequence in E-commerceProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539149(2851-2859)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539149
Wang JMin WHou SMa SZheng YJiang S(2022)LogoDet-3K: A Large-scale Image Dataset for Logo DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/346678018:1(1-19)Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1145/3466780
Torbarina MČop NJelenc L(2021)Logo Shape and Color as Drivers of Change in Brand Evaluation and RecognitionNaše gospodarstvo/Our economy10.2478/ngoe-2021-000467:1(33-45)Online publication date: 18-Apr-2021
https://doi.org/10.2478/ngoe-2021-0004
Wang JZheng YSong JHou SShen HZhuang YSmith JYang YCesar PMetze FPrabhakaran B(2021)Cross-View Representation Learning for Multi-View Logo Classification with Information BottleneckProceedings of the 29th ACM International Conference on Multimedia10.1145/3474085.3475704(4680-4688)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3474085.3475704
Hou QMin WWang JHou SZheng YJiang SShen HZhuang YSmith JYang YCesar PMetze FPrabhakaran B(2021)FoodLogoDet-1500: A Dataset for Large-Scale Food Logo Detection via Multi-Scale Feature Decoupling NetworkProceedings of the 29th ACM International Conference on Multimedia10.1145/3474085.3475289(4670-4679)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3474085.3475289
Cheng BDuan HHou SKarim AJia WZheng Y(2021)An Effective Anchor-Free model with Transformer for Logo DetectionEfficient Logo Detection via Transformer2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI)10.1109/CISAI54367.2021.00045(198-206)Online publication date: Sep-2021
https://doi.org/10.1109/CISAI54367.2021.00045
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