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Invariant Interest Point Detection Based on Variations of the Spinor Tensor
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
IIT, CNR.
2014 (English)In: WSCG, Communication papers proceedings , ISBN 978-80-86943-71-8, 2014, 49-56 p.Conference paper, Published paper (Refereed)
Abstract [en]

Image features are obtained by using some kind of interest point detector, which often is based on a symmetric matrix such as the structure tensor or the Hessian matrix. These features need to be invariant to rotation and to some degree also to scaling in order to be useful for feature matching in applications such as image registration. Recently, the spinor tensor has been proposed for edge detection. It was investigated herein how it also can be used for feature matching and it will be proven that some simplifications, leading to variations of the response function based on the tensor, will improve its characteristics. The result is a set of different approaches that will be compared to the well known methods using the Hessian and the structure tensor. Most importantly the invariance when it comes to rotation and scaling will be compared.

Place, publisher, year, edition, pages
2014. 49-56 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-238896OAI: oai:DiVA.org:uu-238896DiVA: diva2:772698
Conference
WSCG'2014 - 22nd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2014
Available from: 2014-12-17 Created: 2014-12-17 Last updated: 2014-12-19

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CiteExportLink to record
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Output format
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  • asciidoc
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