NDLI: An efficient manual image annotation approach based on tagging and browsing

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Content Provider	ACM Digital Library
Author	Yan, Rong Campbell, Murray Natsev, Apostol
Abstract	This paper investigates new approaches to improve the efficiency of manual image annotation and help users to produce better annotation results in a given amount of time. Although important in practice, this issue has rarely been studied in a quantitative way before. To achieve this, we first propose two time models to analyze the annotation process for two popular manual annotation approaches, i.e., tagging and browsing. The complementary properties of these approaches have inspired us to merge them to develop a hybrid annotation algorithms called frequency-based annotation. Our experiments on large-scale multimedia collections have shown that the proposed algorithm can achieve an up to 40% annotation time reduction compared with the baseline methods. In other words, it can produce considerably better results using the same annotation time.
Starting Page	13
Ending Page	20
Page Count	8
File Format	PDF
ISBN	9781595937827
DOI	10.1145/1290067.1290071
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-09-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Image annotation Browsing Tagging
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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An efficient manual image annotation approach based on tagging and browsing