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Learning an interactive segmentation system

2010

Conference Paper

ei


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.

Author(s): Nickisch, H. and Rother, C. and Kohli, P. and Rhemann, C.
Journal: Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010)
Pages: 274-281
Year: 2010
Month: December
Day: 0
Editors: Chellapa, R. , P. Anandan, A. N. Rajagopalan, P. J. Narayanan, P. Torr
Publisher: ACM Press

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Address: Nw York, NY, USA
Digital: 0
DOI: 10.1145/1924559.1924596
Event Name: Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010)
Event Place: Chennai, India
ISBN: 978-1-4503-0060-5
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{6792,
  title = {Learning an interactive segmentation system},
  author = {Nickisch, H. and Rother, C. and Kohli, P. and Rhemann, C.},
  journal = {Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010)},
  pages = {274-281},
  editors = {Chellapa, R. , P. Anandan, A. N. Rajagopalan, P. J. Narayanan, P. Torr},
  publisher = {ACM Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Nw York, NY, USA},
  month = dec,
  year = {2010},
  month_numeric = {12}
}