Skip to Main content Skip to Navigation
New interface
Conference papers

A 2D Shape Structure for Decomposition and Part Similarity

Kathryn Leonard 1 Geraldine Morin 2, 3 Stefanie Hahmann 4 Axel Carlier 2, 3 
2 IRIT-REVA - Real Expression Artificial Life
IRIT - Institut de recherche en informatique de Toulouse
4 IMAGINE - Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
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.
Document type :
Conference papers
Complete list of metadata

Cited literature [30 references]  Display  Hide  Download
Contributor : Stefanie Hahmann Connect in order to contact the contributor
Submitted on : Saturday, October 1, 2016 - 3:47:32 PM
Last modification on : Friday, November 18, 2022 - 9:26:39 AM
Long-term archiving on: : Monday, January 2, 2017 - 12:53:19 PM


Files produced by the author(s)



Kathryn Leonard, Geraldine Morin, Stefanie Hahmann, Axel Carlier. A 2D Shape Structure for Decomposition and Part Similarity. ICPR 2016 - 23rd International Conference on Pattern Recognition, Dec 2016, Cancun, Mexico. pp.3216-3221, ⟨10.1109/ICPR.2016.7900130⟩. ⟨hal-01374810⟩



Record views


Files downloads