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  Learning an interactive segmentation system

Nickisch, H., Rother C, Kohli, P., & Rhemann, C. (2010). Learning an interactive segmentation system. In Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010) (pp. 274-281). Nw York, NY, USA: ACM Press.

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 Creators:
Nickisch, H1, Author           
Rother C, Kohli, P, Author
Rhemann, C, Author
Chellapa, Editor
R., Editor
Anandan, P., Editor
Rajagopalan, A. N., Editor
Narayanan, P. J., Editor
Torr, P., Editor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 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.

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 Dates: 2010-12
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 978-1-4503-0060-5
URI: http://www.ee.iitm.ac.in/icvgip10/home.html
DOI: 10.1145/1924559.1924596
BibTex Citekey: 6792
 Degree: -

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Title: Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010)
Place of Event: Chennai, India
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Title: Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010)
Source Genre: Proceedings
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Publ. Info: Nw York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 274 - 281 Identifier: -