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

Discriminative structured outputs prediction model and its efficient online learning algorithm

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

4 Author(s)
Yang Wu ; Inst. of Artificial Intell. & Robot., Xi''an Jiaotong Univ., Xi''an, China ; Zejian Yuan ; Yuanliu Liu ; Nanning Zheng

There are two big issues emerging in the field of computer vision: one is the explosively increasing large amount of visual data and the other is the demand of deep labeling of objects and scenes. In this paper, we propose a structured outputs prediction framework equipped with a discriminative model and a corresponding efficient online learning algorithm. Instead of doing simple multiclass classification as usual, we aim at outputting structured labels which means different label confusion mistakes may have different costs. Moreover, the online learning algorithm with efficient updating strategy and compact memory management mechanism makes the framework work well on large visual data. Experiments on two representative datasets show an exemplar application of our model.

Published in:

Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on

Date of Conference:

Sept. 27 2009-Oct. 4 2009

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.