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Provably scale-covariant networks from oriented quasi quadrature measures in cascade
KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST). (Computational Brain Science Lab)ORCID iD: 0000-0002-9081-2170
2019 (English)In: Scale Space and Variational Methods in Computer Vision / [ed] M. Burger, J. Lellmann and J. Modersitzki, Springer Berlin/Heidelberg, 2019, Vol. 11603, p. 328-340Conference paper, Published paper (Refereed)
Abstract [en]

This article presents a continuous model for hierarchical networks based on a combination of mathematically derived models of receptive fields and biologically inspired computations.

Based on a functional model of complex cells in terms of an oriented quasi quadrature combination of first- and second-order directional Gaussian derivatives, we couple such primitive computations in cascade over combinatorial expansions over image orientations. Scale-space properties of the computational primitives are analysed and it is shown that the resulting representation allows for provable scale and rotation covariance.

A prototype application to texture analysis is developed and it is demonstrated that a simplified mean-reduced representation of the resulting QuasiQuadNet leads to promising experimental results on three texture datasets.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2019. Vol. 11603, p. 328-340
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 11603
National Category
Computer Vision and Robotics (Autonomous Systems) Bioinformatics (Computational Biology)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-244788DOI: 10.1007/978-3-030-22368-7_26Scopus ID: 2-s2.0-85068440199ISBN: 9783030223670 (print)OAI: oai:DiVA.org:kth-244788DiVA, id: diva2:1291606
Conference
7th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2019; Hofgeismar; Germany; 30 June 2019 through 4 July 2019
Projects
Scale-space theory for covariant and invariant visual perception
Funder
Swedish Research Council, 2018-03586
Note

QC 20190305

Available from: 2019-02-25 Created: 2019-02-25 Last updated: 2019-08-08Bibliographically approved

Open Access in DiVA

fulltext(1179 kB)92 downloads
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Other links

Publisher's full textScopuspreprint at arXiv:1903.00289Conference webpage

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