PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Parametrization and computations in shape spaces with area and boundary invariants
Subramanian Ramamoorthy, Benjamin Kuipers and Lothar Wenzel
In: Fall Workshop on Computational and Combinatorial Geometry, 10-11 Nov 2006, Northampton, USA.

Abstract

Shape spaces play an important role in several applications in robotics, most notably by providing a manifold structure on which to perform motion planning, control, behavior discovery and related algorithmic operations. Many classical approaches to defining shape spaces are not well suited to the needs of robotics. In this abstract, we outline an approach to defining shape spaces that address the needs of such problems, which often involve constraints on area/volume, perimeter/boundary, etc. Using the simple example of the space of constant-area and constant-perimeter triangles, which are represented as Riemannian manifolds, we demonstrate efficient solutions to problems involving continuous shape evolution, optimal sampling, etc.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5396
Deposited By:Subramanian Ramamoorthy
Deposited On:28 April 2009