Abstract:
In computational geometry, the elastic geometric shape matching (EGSM) problem class is a generalisation of the well-known geometric shape matching problem class: Given two geometric shapes, the `pattern' and the `model', find a single transformation from a given transformation class that, if applied to the pattern, minimizes the distance between the transformed pattern and the model with respect to a suitable distance measure.
Reference:
An FPTAS for an Elastic Shape Matching Problem with Cyclic Neighborhoods (Christian Knauer, Luise Sommer, Fabian Stehn), In Computational Science and Its Applications -- ICCSA 2018 (Osvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Elena Stankova, Carmelo M. Torre, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan, Eufemia Tarantino, Yeonseung Ryu, eds.), Springer International Publishing, 2018. (Best paper award)
Bibtex Entry:
@InProceedings{conf/10.1007/978-3-319-95165-2_30,
author="Knauer, Christian
and Sommer, Luise
and Stehn, Fabian",
editor="Gervasi, Osvaldo
and Murgante, Beniamino
and Misra, Sanjay
and Stankova, Elena
and Torre, Carmelo M.
and Rocha, Ana Maria A.C.
and Taniar, David
and Apduhan, Bernady O.
and Tarantino, Eufemia
and Ryu, Yeonseung",
title="An FPTAS for an Elastic Shape Matching Problem with Cyclic Neighborhoods",
booktitle="Computational Science and Its Applications -- ICCSA 2018",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="425--443",
abstract="In computational geometry, the elastic geometric shape matching (EGSM) problem class is a generalisation of the well-known geometric shape matching problem class: Given two geometric shapes, the `pattern' and the `model', find a single transformation from a given transformation class that, if applied to the pattern, minimizes the distance between the transformed pattern and the model with respect to a suitable distance measure.",
isbn="978-3-319-95165-2",
note="Best paper award"
}