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Crystal Vision-Applications of Point Groups in Computer Vision
Linköping University, Department of Science and Technology, Digital Media. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-7557-4904
2007 (English)In: Computer Vision – ACCV 2007: 8th Asian Conference on Computer Vision, Tokyo, Japan, November 18-22, 2007, Proceedings, Part II / [ed] Yasushi Yagi, Sing Bing Kang, In So Kweon, Hongbin Zha, Springer Berlin/Heidelberg, 2007, 744-753 p.Conference paper (Refereed)
Abstract [en]

Methods from the representation theory of finite groups are used to construct efficient processing methods for the special geometries related to the finite subgroups of the rotation group. We motivate the use of these subgroups in computer vision, summarize the necessary facts from the representation theory and develop the basics of Fourier theory for these geometries. We illustrate its usage for data compression in applications where the processes are (on average) symmetrical with respect to these groups. We use the icosahedral group as an example since it is the largest finite subgroup of the 3D rotation group. Other subgroups with fewer group elements can be studied in exactly the same way.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2007. 744-753 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 4844
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-39225DOI: 10.1007/978-3-540-76390-1_73ISI: 000252603100073Local ID: 47466ISBN: 978-3-540-76389-5 (print)ISBN: 978-3-540-76390-1 (online)OAI: diva2:260074
8th Asian Conference on Computer Vision, Tokyo, Japan, November 18-22, 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2016-08-31Bibliographically approved

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Lenz, Reiner
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