@inproceedings{c6127d3aeaed4398b446b2bea6ab3444,
title = "An experimental comparison of discrete and continuous shape optimization methods",
abstract = "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 L 2-norm in the length term.",
author = "Maria Klodt and Thomas Schoenemann and Kalin Kolev and Marek Schikora and Daniel Cremers",
year = "2008",
doi = "10.1007/978-3-540-88682-2_26",
language = "English",
isbn = "3540886818",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 1",
pages = "332--345",
booktitle = "Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Proceedings",
edition = "PART 1",
note = "10th European Conference on Computer Vision, ECCV 2008 ; Conference date: 12-10-2008 Through 18-10-2008",
}