A 2D Shape Structure for Decomposition and Part Similarity

Kathryn Leonard, Geraldine Morin, Stefanie Hahmann, Axel Carlier

International Conference on Pattern Recognition (ICPR), 2016

Hierarchies for similar shapes (dancers) in different poses.

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.