short-paper

Automatic image tagging via category label and web data

Authors:

Shenghua Gao,

Zhengxiang Wang,

Liang-Tien Chia,

Ivor Wai-Hung TsangAuthors Info & Claims

MM '10: Proceedings of the 18th ACM international conference on Multimedia

Pages 1115 - 1118

https://doi.org/10.1145/1873951.1874164

Published: 25 October 2010 Publication History

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Abstract

Image tagging is an important technique for the image content understanding and text based image processing. Given a selection of images, how to tag these images efficiently and effectively is an interesting problem. In this paper, a novel semi-auto image tagging technique is proposed: By assigning each image a category label first, our method can automatically recommend those promising tags to each image by utilizing existing vast web data. The main contributions of our paper can be highlighted as follows: (i) By assigning each image a category label, our method can automatically recommend other tags to the image, thus reducing the human annotation efforts. Meanwhile, our method guarantee tags' diversity due to abundant web data. (ii) We use sparse coding to automatically select those semantically related images for tag propagation. (iii) Local & global ranking agglomeration will make our method robust to noisy tags. We use Event dataset as the images to be tagged, and crawled Flickr images with their associated tags according to the category label in Event dataset as the auxiliary web data. Experimental results show that our method achieves promising performance for image tagging, which proves the effectiveness of our method.

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Cited By

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Shrivastava RDeepak G(2023)MLSM: A Metadata Driven Learning Infused Semantics Oriented Model for Web Image Recommendation via TagsComputational Intelligence and Network Systems10.1007/978-3-031-48984-6_4(38-46)Online publication date: 16-Dec-2023
https://doi.org/10.1007/978-3-031-48984-6_4
Contu FDemontis ADessì SMuscas MRiboni D(2021)AI-Based Analysis of Policies and Images for Privacy-Conscious Content SharingFuture Internet10.3390/fi1306013913:6(139)Online publication date: 21-May-2021
https://doi.org/10.3390/fi13060139
Wang DMao K(2019)Learning Semantic Text Features for Web Text-Aided Image ClassificationIEEE Transactions on Multimedia10.1109/TMM.2019.292062021:12(2985-2996)Online publication date: Dec-2019
https://doi.org/10.1109/TMM.2019.2920620
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Index Terms

Automatic image tagging via category label and web data
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
    2. Retrieval tasks and goals

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Information

Published In

MM '10: Proceedings of the 18th ACM international conference on Multimedia

October 2010

1836 pages

ISBN:9781605589336

DOI:10.1145/1873951

General Chairs:
Alberto del Bimbo
University of Florence, Italy
,
Shih-Fu Chang
Columbia University, USA
,
Program Chair:
Arnold Smeulders
University of Amsterdam, NL

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 October 2010

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MM '10

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SIGMM

MM '10: ACM Multimedia Conference

October 25 - 29, 2010

Firenze, Italy

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Shrivastava RDeepak G(2023)MLSM: A Metadata Driven Learning Infused Semantics Oriented Model for Web Image Recommendation via TagsComputational Intelligence and Network Systems10.1007/978-3-031-48984-6_4(38-46)Online publication date: 16-Dec-2023
https://doi.org/10.1007/978-3-031-48984-6_4
Contu FDemontis ADessì SMuscas MRiboni D(2021)AI-Based Analysis of Policies and Images for Privacy-Conscious Content SharingFuture Internet10.3390/fi1306013913:6(139)Online publication date: 21-May-2021
https://doi.org/10.3390/fi13060139
Wang DMao K(2019)Learning Semantic Text Features for Web Text-Aided Image ClassificationIEEE Transactions on Multimedia10.1109/TMM.2019.292062021:12(2985-2996)Online publication date: Dec-2019
https://doi.org/10.1109/TMM.2019.2920620
Abd El-Ghany SElminir HRiad A(2019)An Improved Image Annotation and Retrieval System Using Hybrid Based Semantic and Context Data Analysis2019 International Conference on Computer and Information Sciences (ICCIS)10.1109/ICCISci.2019.8716397(1-5)Online publication date: Apr-2019
https://doi.org/10.1109/ICCISci.2019.8716397
Feng XWu SZhou W(2017)Multi-Hypergraph Consistent Sparse CodingACM Transactions on Intelligent Systems and Technology10.1145/30788468:6(1-25)Online publication date: 24-Jul-2017
https://dl.acm.org/doi/10.1145/3078846
Haifeng GShoubao SZhoubao S(2017)Image tag recommendation based on friendshipsMultimedia Tools and Applications10.1007/s11042-016-3802-776:13(14581-14597)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s11042-016-3802-7
Gao STsang IChia L(2013)Laplacian Sparse Coding, Hypergraph Laplacian Sparse Coding, and ApplicationsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2012.6335:1(92-104)Online publication date: 1-Jan-2013
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Feng ZJin RJain A(2013)Large-Scale Image Annotation by Efficient and Robust Kernel Metric Learning2013 IEEE International Conference on Computer Vision10.1109/ICCV.2013.203(1609-1616)Online publication date: Dec-2013
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Wang WLang CFeng S(2013)Contextualizing Tag Ranking and Saliency Detection for Social ImagesAdvances in Multimedia Modeling10.1007/978-3-642-35728-2_41(428-435)Online publication date: 2013
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Karlsen RAndersen A(2013)NFC-Based Image AnnotationTrends in Mobile Web Information Systems10.1007/978-3-319-03737-0_9(72-85)Online publication date: 2013
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A Hybrid Probabilistic Model for Unified Collaborative and Content-Based Image Tagging

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