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Efficient computation of channel-coded feature maps through piecewise polynomials
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-6096-3648
2009 (English)In: Image and Vision Computing, ISSN 0262-8856, Vol. 27, no 11, 1688-1694 p.Article in journal (Refereed) Published
Abstract [en]

Channel-coded feature maps (CCFMs) represent arbitrary image features using multi-dimensional histograms with soft and overlapping bins. This representation can be seen as a generalization of the SIFT descriptor, where one advantage is that it is better suited for computing derivatives with respect to image transformations. Using these derivatives, a local optimization of image scale, rotation and position relative to a reference view can be computed. If piecewise polynomial bin functions are used, e.g. B-splines, these histograms can be computed by first encoding the data set into a histogram-like representation with non-overlapping multi-dimensional monomials as bin functions. This representation can then be processed using multi-dimensional convolutions to obtain the desired representation. This allows to reuse much of the computations for the derivatives. By comparing the complexity of this method to direct encoding, it is found that the piecewise method is preferable for large images and smaller patches with few channels, which makes it useful, e.g. in early steps of coarse-to-fine approaches.

Place, publisher, year, edition, pages
2009. Vol. 27, no 11, 1688-1694 p.
Keyword [en]
Channel-coded feature maps; Feature histograms; Piecewise polynomials; Soft histograms; Splines
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-21197DOI: 10.1016/j.imavis.2008.11.002OAI: oai:DiVA.org:liu-21197DiVA: diva2:240892
Note
Original Publication: Erik Jonsson and Michael Felsberg, Efficient computation of channel-coded feature maps through piecewise polynomials, 2009, Image and Vision Computing, (27), 11, 1688-1694. http://dx.doi.org/10.1016/j.imavis.2008.11.002 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/ Available from: 2009-09-30 Created: 2009-09-30 Last updated: 2016-05-04

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