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Publications:Directionality Features and the Structure Tensor
Abstract <p>Many low-level features, as well <p>Many low-level features, as well as varyingmethods of extraction and interpretation rely on directionalityanalysis (for example the Hough transform, Gabor filters,SIFT descriptors and the structure tensor). The theoryof the gradient based structure tensor (a.k.a. the secondmoment matrix) is a very well suited theoretical platform inwhich to analyze and explain the similarities and connections(indeed often equivalence) of supposedly different methodsand features that deal with image directionality. Of specialinterest to this study is the SIFT descriptors (histogram oforiented gradients, HOGs). Our analysis of interrelationshipsof prominent directionality analysis tools offers thepossibility of computation of HOGs without binning, in analgorithm of comparative time complexity.</p> of comparative time complexity.</p>
Author Stefan Karlsson + , Josef Bigun +
Conference SSBA 2010 Symposium i bildanalys, Uppsala 11-12 mars
Diva http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:391385
PublicationType Conference Paper  +
Title Directionality Features and the Structure Tensor  +
Year 2010  +
Has queryThis property is a special property in this wiki. Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor + , Publications:Directionality Features and the Structure Tensor +
Categories Publication  +
Modification dateThis property is a special property in this wiki. 13 March 2014 11:50:18  +
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