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A 2D Shape Structure for Decomposition and Part Similarity

Kathryn Leonard 1 Geraldine Morin 2 Stefanie Hahmann 3 Axel Carlier 2
2 IRIT-REVA - Real Expression Artificial Life
IRIT - Institut de recherche en informatique de Toulouse
3 IMAGINE [2016-2019] - Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments [2016-2019]
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann , Grenoble INP [2007-2019] - Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019]
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.
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Submitted on : Saturday, October 1, 2016 - 3:47:32 PM
Last modification on : Tuesday, October 6, 2020 - 12:44:47 PM
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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⟩



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