Talks and Poster Presentations (with Proceedings-Entry):
H. Nickisch, C. Rother, P. Kohli, C. Rhemann:
"Learning an Interactive Segmentation System";
Talk: Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP),
- 2010-12-15; in: "Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP)",
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.
Interactive segmentation, interactive learning, SVMstruct
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.