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An efficiently computable metric for comparing polygonal shapes
Abstract
A method for comparing polygons that is a metric, invariant under translation, rotation, and change of scale, reasonably easy to compute, and intuitive is presented. The method is based on the L/sub 2/ distance between the turning functions of the two polygons. It works for both convex and nonconvex polygons and runs in time O(mn log mn), where m is the number of vertices in one polygon and n is the number of vertices in the other. Some examples showing that the method produces answers that are intuitively reasonable are presented.>
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Cited by
Comparing images using the Hausdorff distance
Huttenlocher, D. P., Klanderman, G. A., & Rucklidge, W. J. (1993) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.232073 · Cited by 4,545
Self-citationFunkhouser, T., Min, P., Kazhdan, M., Chen, J., Halderman, A., Dobkin, D., & Jacobs, D. (2003) · ACM Transactions on Graphics · doi:10.1145/588272.588279 · Cited by 935
Shape matching: similarity measures and algorithms
Veltkamp, R. C. (2002) · Proceedings International Conference on Shape Modeling and Applications · doi:10.1109/sma.2001.923389 · Cited by 434
Active Boundary Component Models for robotic dressing assistance
Twardon, L., & Ritter, H. (2016) · 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759436 · Cited by 18
Metadata
- Authors
- Arkin, E. M., Chew, L. P., Huttenlocher, D. P., Kedem, K., & Mitchell, J. S. B.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1991-03
- Volume
- 13
- Issue
- 3
- Pages
- 209-216
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2071867759
- Cited by
- 628
- References
- 0
- FWCI
- 11.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- Arkin, E. M., Chew, L. P., Huttenlocher, D. P., Kedem, K., & Mitchell, J. S. B. (1991). An efficiently computable metric for comparing polygonal shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.75509
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