Bibtex de la publication

@InProceedings{ Le2016.7,
author = {Leonard, Kathryn and Morin, GĂ©raldine and Hahmann, Stefanie and Carlier, Axel},
title = "{A 2D Shape Structure for Decomposition and Part Similarity (regular paper)}",
booktitle = "{International Conference on Pattern Recognition (ICPR), Cancun, Mexico., 04/12/2016-08/12/2016}",
year = {2016},
month = {décembre},
publisher = {IEEE},
address = {http://www.ieee.org/},
pages = {(on line)},
language = {anglais},
URL = {https://hal.inria.fr/hal-01374810/document},
abstract = {This paper presents a multilevel analysis of 2D shapes and uses it to find similarities between the different parts of a shape. Such an analysis is important for many applications such as shape comparison, editing, and compression. Our robust and stable method decomposes a shape into parts, determines a parts hierarchy, and measures similarity between parts based on a salience measure on the medial axis, the Weighted Extended Distance Function, providing a multi-resolution partition of the shape that is stable across scale and articulation. Comparison with an extensive user study on the MPEG-7 database demonstrates that our geometric results are consistent with user perception.}
}