A Statistical Theory of Shape
(1998) Advances in Pattern Recognition. Joint IAPR International Workshops. SSPR'98 and SPR'98. Proceedings p.677-686- Abstract
- We study the statistical theory of shape for ordered finite point configurations, or otherwise stated, the uncertainty of geometric invariants. A general approach for defining shape and finding its density, expressed in the densities for the individual points, is developed. Some examples that can be computed analytically are given, including both affine and positive similarity shape. Projective shape and projective invariants are important topics in computer vision and are also discussed
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/787227
- author
- Berthilsson, Rikard LU
- organization
- publishing date
- 1998
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- uncertain systems, statistical analysis, computational geometry, computer vision
- host publication
- Advances in Pattern Recognition. Joint IAPR International Workshops SSPR'98 and SPR'98. Proceedings
- pages
- 677 - 686
- publisher
- Springer
- conference name
- Advances in Pattern Recognition. Joint IAPR International Workshops. SSPR'98 and SPR'98. Proceedings
- conference location
- Sydney, NSW, Australia
- conference dates
- 1998-08-11 - 1998-08-13
- external identifiers
-
- scopus:22044447963
- ISBN
- 3 540 64858 5
- language
- English
- LU publication?
- yes
- id
- 95c9b436-5bea-4cdb-ba9e-0710b5ddfcad (old id 787227)
- date added to LUP
- 2016-04-04 11:29:29
- date last changed
- 2022-01-29 21:58:38
@inproceedings{95c9b436-5bea-4cdb-ba9e-0710b5ddfcad, abstract = {{We study the statistical theory of shape for ordered finite point configurations, or otherwise stated, the uncertainty of geometric invariants. A general approach for defining shape and finding its density, expressed in the densities for the individual points, is developed. Some examples that can be computed analytically are given, including both affine and positive similarity shape. Projective shape and projective invariants are important topics in computer vision and are also discussed}}, author = {{Berthilsson, Rikard}}, booktitle = {{Advances in Pattern Recognition. Joint IAPR International Workshops SSPR'98 and SPR'98. Proceedings}}, isbn = {{3 540 64858 5}}, keywords = {{uncertain systems; statistical analysis; computational geometry; computer vision}}, language = {{eng}}, pages = {{677--686}}, publisher = {{Springer}}, title = {{A Statistical Theory of Shape}}, year = {{1998}}, }