By Topic

Techniques and data structures for efficient multimedia retrieval based on similarity

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
$33 $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

1 Author(s)
Guojun Lu ; Gippsland Sch. of Comput. & Inf. Technol., Monash Univ., Churchill, Australia

As more and more information is captured and stored in digital form, many techniques and systems have been developed for indexing and retrieval of text documents, audio, images, and video. The retrieval is normally based on similarities between extracted feature vectors of the query and stored items. Feature vectors are usually multidimensional. When the number of stored objects and/or the number of dimensions of the feature vectors are large, it will be too slow to linearly search all stored feature vectors to find those that satisfy the query criteria. Techniques and data structures are thus required to organize feature vectors and manage the search process so that objects relevant to the query can be located quickly. This paper provides a survey of these techniques and data structures.

Published in:

Multimedia, IEEE Transactions on  (Volume:4 ,  Issue: 3 )