TY - GEN

T1 - An efficiently computable metric for comparing polygonal shapes

AU - Arkin, Esther M.

AU - Chew, L. Paul

AU - Huttenlocher, David P.

AU - Kedem, Klara

AU - Mitchell, Joseph S.B.

N1 - Funding Information:
*Partially supported by NSF grants DMC 8451884, ECSE 8857642 and DMS 8903304. tSupported by DARPA under ONR contract NOOlPSBK-0591, NSF grant DMC-86-17355 and ONR contract N00014-86-K-0281. SPartially supported by NSF grants IRI-8710858 and ECSE 8857642, and by a grant from Hughes Research Laboratories. #Cornell University, Ithaca, NY 14853.

PY - 1990/1/1

Y1 - 1990/1/1

N2 - Model-based recognition is concerned with comparing a shape A, which is stored as a model for some particular object, with a shape B, which is found to exist in an image. If A and B are close to being the same shape, then a vision system should report a match and return a measure of how good that match is. To be useful this measure should satisfy a number of properties, including: (1) it should be a metric, (2) it should be invariant under translation, rotation, and change-of-scale, (3) it should be reasonably easy to compute, and (4) it should match our intuition (i.e., answers should be similar to those that a person might give). We develop a method for comparing polygons that has these properties. The method works for both convex and nonconvex polygons and runs in time 0(mn log mn) where m is the number of vertices in one polygon and n is the number of vertices in the other. We also present some examples to show that the method produces answers that are intuitively reasonable.

AB - Model-based recognition is concerned with comparing a shape A, which is stored as a model for some particular object, with a shape B, which is found to exist in an image. If A and B are close to being the same shape, then a vision system should report a match and return a measure of how good that match is. To be useful this measure should satisfy a number of properties, including: (1) it should be a metric, (2) it should be invariant under translation, rotation, and change-of-scale, (3) it should be reasonably easy to compute, and (4) it should match our intuition (i.e., answers should be similar to those that a person might give). We develop a method for comparing polygons that has these properties. The method works for both convex and nonconvex polygons and runs in time 0(mn log mn) where m is the number of vertices in one polygon and n is the number of vertices in the other. We also present some examples to show that the method produces answers that are intuitively reasonable.

UR - http://www.scopus.com/inward/record.url?scp=84944984554&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84944984554

T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms

SP - 129

EP - 137

BT - Proceedings of the 1st Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 1990

PB - Association for Computing Machinery

T2 - 1st Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 1990

Y2 - 22 January 1990 through 24 January 1990

ER -