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ECCV
2008
Springer

An Experimental Comparison of Discrete and Continuous Shape Optimization Methods

14 years 5 months ago
An Experimental Comparison of Discrete and Continuous Shape Optimization Methods
Shape optimization is a problem which arises in numerous computer vision problems such as image segmentation and multiview reconstruction. In this paper, we focus on a certain class of binary labeling problems which can be globally optimized both in a spatially discrete setting and in a spatially continuous setting. The main contribution of this paper is to present a quantitative comparison of the reconstruction accuracy and computation times which allows to assess some of the strengths and limitations of both approaches. We also present a novel method to approximate length regularity in a graph cut based framework: Instead of using pairwise terms we introduce higher order terms. These allow to represent a more accurate discretization of the L2-norm in the length term.
Maria Klodt, Thomas Schoenemann, Kalin Kolev, Mare
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 2008
Where ECCV
Authors Maria Klodt, Thomas Schoenemann, Kalin Kolev, Marek Schikora, Daniel Cremers
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