ECCV 2010: Computer Vision – ECCV 2010 pp 672-686

# Shape Analysis of Planar Objects with Arbitrary Topologies Using Conformal Geometry

• Lok Ming Lui
• Wei Zeng
• Shing-Tung Yau
• Xianfeng Gu
Conference paper

DOI: 10.1007/978-3-642-15555-0_49

Volume 6315 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Lui L.M., Zeng W., Yau ST., Gu X. (2010) Shape Analysis of Planar Objects with Arbitrary Topologies Using Conformal Geometry. In: Daniilidis K., Maragos P., Paragios N. (eds) Computer Vision – ECCV 2010. ECCV 2010. Lecture Notes in Computer Science, vol 6315. Springer, Berlin, Heidelberg

## Abstract

The study of 2D shapes is a central problem in the field of computer vision. In 2D shape analysis, classification and recognition of objects from their observed silhouettes are extremely crucial and yet difficult. It usually involves an efficient representation of 2D shape space with natural metric, so that its mathematical structure can be used for further analysis. Although significant progress has been made for the study of 2D simply-connected shapes, very few works have been done on the study of 2D objects with arbitrary topologies. In this work, we propose a representation of general 2D domains with arbitrary topologies using conformal geometry. A natural metric can be defined on the proposed representation space, which gives a metric to measure dissimilarities between objects. The main idea is to map the exterior and interior of the domain conformally to unit disks and circle domains, using holomorphic 1-forms. A set of diffeomorphisms from the unit circle $$\mathbb{S}^1$$ to itself can be obtained, which together with the conformal modules are used to define the shape signature. We prove mathematically that our proposed signature uniquely represents shapes with arbitrary topologies. We also introduce a reconstruction algorithm to obtain shapes from their signatures. This completes our framework and allows us to move back and forth between shapes and signatures. Experiments show the efficacy of our proposed algorithm as a stable shape representation scheme.

## Supplementary material

978-3-642-15555-0_49_MOESM1_ESM.pdf (1.2 mb)
Electronic Supplementary Material (1,206 KB)

## Authors and Affiliations

• Lok Ming Lui
• 1
• Wei Zeng
• 2
• 3
• Shing-Tung Yau
• 1
• Xianfeng Gu
• 3
1. 1.Department of MathematicsHarvard UniversityCambridgeUSA
2. 2.Department of Computer ScienceWayne State UniversityDetroitUSA
3. 3.Department of Computer ScienceSUNY Stony BrookStony BrookUSA