Discrete Geometric Shapes: Matching, Interpolation, and Approximation

A Survey

Helmut Alt
Institut für Informatik
Freie Universität Berlin
Takustr. 9, 14195 Berlin
email: alt@inf.fu-berlin.de

Leonidas J. Guibas
Computer Science Department
Stanford University
Stanford, CA 94305, USA
email: guibas@cs.stanford.edu

Report B 96-11
December 1996

In this survey we consider geometric techniques which have been used to measure the similarity or distance between shapes, as well as to approximate shapes, or interpolate between shapes. Shape is a modality which plays a key role in many disciplines, ranging from computer vision to molecular biology. We focus on algorithmic techniques based on computational geometry that have been developed for shape matching, simplification, and morphing.

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