Introduction to Image Annotation

Title:

Introduction to Image Annotation

Access Right:

Open Access

Created on:

08/08/2016

Language:

English

Keywords:

Metadata processing, Models and Ontologies

Contributor:

Preserveware Editor

Date:

15/05/2017

Metrics:

693 views , 14 Downloads
Introduction to the background of image annotation.

Expected learning outcomes

Understanding the background of image annotation.

What is the target audience?

  • Digital Preservation professionals and students who are interested in learning more about cutting edge technologies in this area, but who are ultimately interested in the application of these tools into their own work.
  • Researchers exploring solutions for data management, digital preservation and image annotation
  • Teachers/trainers in this field
  • Solution providers for organisations in demand of solutions for data / repository management and digital preservation

Level of advancement/ prerequisites

Basic understanding of metadata

Material chapters

  1. Image annotation background
  2. Challenges of image annotation
  3. Approaches to image annotation

Time required for completion

8 hours

​Supplementary reading

M. J. Huiskes, B. Thomee, and M. S. Lew, “New trends and ideas in visual concept detection: The MIS Flickr retrieval evaluation initiative,” in Proc. Int. Conf. Multimedia Inf. Retrieval, 2010, pp. 527–536. Available: http://doi.acm.org/10.1145/1743384.1743475

Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg and Li Fei-Fei, æImageNet Large Scale Visual Recognition Challenge”, International Journal of Computer Vision, 2015.http://link.springer.com/article/10.1007/s11263-015-0816-y?sa_campaign=email/event/articleAuthor/onlineFirst

B. Thomee et al., “YFCC100M: The new data in multimedia research,” Commun. ACM, vol. 59, no. 2, pp. 64–73, Jan. 2016. Available: http://doi.acm.org/10.1145/2812802

Xirong Li, Tiberio Uricchio, Lamberto Ballan, Marco Bertini, Cees G. M. Snoek, Alberto Del Bimbo,“Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval”, ACM Computing Surveys (CSUR), Volume 49, Issue 1, 14:1-14:39, June 2016. (https://arxiv.org/abs/1503.08248).

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