English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Learning an interactive segmentation system

Nickisch, H., Rother, C., Kohli, P., & Rhemann, C. (2010). Learning an interactive segmentation system. In R. Chellapa, P. Anandan, A. Rajagopalan, P. Narayanan, & P. Torr (Eds.), ICVGIP '10: Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing (pp. 274-281). Nw York, NY, USA: ACM Press.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BD30-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0002-7E30-B
Genre: Conference Paper

Files

show Files

Locators

show
hide
Locator:
https://dl.acm.org/citation.cfm?doid=1924559.1924596 (Publisher version)
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Nickisch, H1, Author           
Rother, C1, 2, Author
Kohli, P, Author
Rhemann, C, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: Many successful applications of computer vision to image or video manipulation are interactive by nature. However, parameters of such systems are often trained neglecting the user. Traditionally, interactive systems have been treated in the same manner as their fully automatic counterparts. Their performance is evaluated by computing the accuracy of their solutions under some fixed set of user interactions. This paper proposes a new evaluation and learning method which brings the user in the loop. It is based on the use of an active robot user -- a simulated model of a human user. We show how this approach can be used to evaluate and learn parameters of state-of-the-art interactive segmentation systems. We also show how simulated user models can be integrated into the popular max-margin method for parameter learning and propose an algorithm to solve the resulting optimisation problem.

Details

show
hide
Language(s):
 Dates: 2010-12
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1145/1924559.1924596
BibTex Citekey: 6792
 Degree: -

Event

show
hide
Title: Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010)
Place of Event: Chennai, India
Start-/End Date: 2010-12-12 - 2010-12-15

Legal Case

show

Project information

show

Source 1

show
hide
Title: ICVGIP '10: Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Source Genre: Proceedings
 Creator(s):
Chellapa, R, Editor
Anandan, P, Editor
Rajagopalan, AN, Editor
Narayanan, PJ, Editor
Torr, P, Editor
Affiliations:
-
Publ. Info: Nw York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 274 - 281 Identifier: ISBN: 978-1-4503-0060-5