Cart (Loading....) | Create Account
Close category search window
 

Typicality-Based Visual Search Reranking

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

5 Author(s)
Yuan Liu ; Dept. of Electron. Eng. & Inf. Sci., Univ. of Sci. & Technol. of China, Hefei, China ; Tao Mei ; Meng Wang ; Xiuqing Wu
more authors

Most existing approaches to visual search reranking predominantly focus on mining information only from the initial ranking order on the basis of pseudo-relevance feedback. However, the initial ranking order cannot always provide enough cues for reranking by itself due to an unsatisfying visual search performance. This letter presents a novel approach to visual search reranking by selecting typical examples to build the reranking model. Observing that typical examples are mostly clearly visible, fill the majority of the visual documents or appear in one of several common poses, by using these examples informed classifiers would generally be more robust to noisy testing cases that may include occlusions, illumination changes or other factors. We first define the typicality on the basis of data distribution, and then theoretically formalize the example selection as an optimization problem on the basis of the example typicality and propose a close-form solution. Based on the selected examples, we build the reranking model by using a support vector machine. Empirically, we conduct extensive experiments on a real-world image set and a benchmark video set, and shows significant and consistent improvements over the state-of-the-art works.

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:20 ,  Issue: 5 )

Date of Publication:

May 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.