By Topic

Crowdsourcing annotation: Modelling keywords using low level features

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Theodosiou, Z. ; Dept. of Commun. & Internet Studies, Cyprus Univ. of Technol., Limassol, Cyprus ; Tsapatsoulis, N.

Tagging large collections is often prohibitive and manual tags are known to be imprecise, ambiguous, inconsistent and subject to many variations. A possible way to alleviate these problems and improve the annotation quality is to obtain multiple annotations per image by assigning several annotators into the task. In the current work we present an approach to model the view of several annotators using four MPEG-7 descriptors and a well known data classifier. We apply keywords modelling to the annotation data collected in the framework of Commandaria project where sixteen non-expert users annotated a set of a hundred images using a predefined set of keywords. The images sharing a common keyword are grouped together and used for the creation of the visual model corresponds to this keyword. Finally, the created models used to classify the images into the keyword classes in terms of 2-classes combinations using the 10-fold cross-validation technique. The experimental results are examined under two perspectives: First, in terms of the separation ability of the various keyword classes and second, in terms of the efficiency of the four visual descriptors as far as the image classification task is concerned.

Published in:

Internet Multimedia Systems Architecture and Application (IMSAA), 2011 IEEE 5th International Conference on

Date of Conference:

12-13 Dec. 2011