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Tag & Link: Supporting Regional and Relational Tagging in Images with Direct Annotation

Published: 18 April 2015 Publication History

Abstract

Image tagging is crucial to the use of digital photos and value-added applications. We present Tag & Link, a tagging interface featured direct annotations to collect fine-grained descriptions of image content that can be hard to obtain otherwise. Tag & Link provides a set of drawing tools, allowing users to directly specify regions of interest (ROIs), and the relations between different ROIs on an image. Through a crowdsourcing study, we show that Tag & Link enhances tagging productivity and helps collect annotations on small objects and behaviors embedded in images. We demonstrate the value of direct annotation on the elicitation of fine-grained human knowledge of image content.

References

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Ames, M., & Naaman, M. Why we tag: Motivation for annotation in mobile and online media. In Proc. CHI 2007, ACM Press (2007).
[2]
Dong, W., & Fu, W.-T. Cultural difference in image tagging. In Proc. CHI 2010, ACM Press (2010).
[3]
Karpathy, A., & Li, F-F. Deep visual-semantic alignments for generating image descriptions. http://cs.stanford.edu/people/karpathy/deepimagesent
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Klavans, J., Guerra, P., LaPlante, R., Stein, R. & Bachta, E. Beyond Flickr: Not all image tagging is created equal. In AAAI 2011 Workshop: LanguageAction Tools for Cognitive Artificial Agents (2011).
[5]
Sen, S., Lam, S., Rashid, A. M., Cosley, D., Frankowski, D., Osterhouse, J., Harper, F. M., & Riedl, J. Tagging, communities, vocabulary, evolution. In Proc. CSCW 2006, ACM Press (2006).
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Shneiderman, B., & Kang, H. Direct annotation: A drag-n-drop strategy for labeling photos. In Proc. Information Visualization (InfoViz) (2000).
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von Ahn, L., & Dabbish, L. Labeling images with a computer game. In Proc. CHI 2004, ACM Press (2004). Figure 6. Percentage of transitive verbs (number of transitive verbs / number of labels) by condition.

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  1. Tag & Link: Supporting Regional and Relational Tagging in Images with Direct Annotation

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      cover image ACM Conferences
      CHI EA '15: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems
      April 2015
      2546 pages
      ISBN:9781450331463
      DOI:10.1145/2702613
      Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 18 April 2015

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      Author Tags

      1. content analysis
      2. crowdsourcing
      3. image tagging
      4. knowledge acquisition

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      • Work in progress

      Funding Sources

      • Google
      • Ministry of Science and Technology Taiwan

      Conference

      CHI '15
      Sponsor:
      CHI '15: CHI Conference on Human Factors in Computing Systems
      April 18 - 23, 2015
      Seoul, Republic of Korea

      Acceptance Rates

      CHI EA '15 Paper Acceptance Rate 379 of 1,520 submissions, 25%;
      Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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      CHI 2025
      ACM CHI Conference on Human Factors in Computing Systems
      April 26 - May 1, 2025
      Yokohama , Japan

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      • (2023)User Preference and Performance using Tagging and Browsing for Image LabelingProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580926(1-13)Online publication date: 19-Apr-2023
      • (2021)A survey of image labelling for computer vision applicationsJournal of Business Analytics10.1080/2573234X.2021.19088614:2(91-110)Online publication date: 18-Apr-2021
      • (2018)Click-SearchJournal of Visual Languages and Computing10.1016/j.jvlc.2016.09.00246:C(12-19)Online publication date: 1-Jun-2018
      • (2016)Gamification for informal terms lexicon buildingProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.5555/3192424.3192678(1372-1373)Online publication date: 18-Aug-2016
      • (2016)Gamification for informal terms lexicon building2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)10.1109/ASONAM.2016.7752418(1372-1373)Online publication date: Aug-2016

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