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BIMP: A real-time biological model of multi-scale keypoint detection in V1

2015Journal article Open access
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dc.contributor.authorTerzic, Kasim
dc.contributor.authorRodrigues, J. M. F.
dc.contributor.authordu Buf, J. M. H.
dc.date.accessioned2015-11-04T12:04:38Z
dc.date.available2016-03-01T01:30:09Z
dc.date.issued2015
dc.description.abstractWe present an improved, biologically inspired and multiscale keypoint operator. Models of single- and double-stopped hypercomplex cells in area V1 of the mammalian visual cortex are used to detect stable points of high complexity at multiple scales. Keypoints represent line and edge crossings, junctions and terminations at fine scales, and blobs at coarse scales. They are detected by applying first and second derivatives to responses of complex cells in combination with two inhibition schemes to suppress responses along lines and edges. A number of optimisations make our new algorithm much faster than previous biologically inspired models, achieving real-time performance on modern GPUs and competitive speeds on CPUs. In this paper we show that the keypoints exhibit state-of-the-art repeatability in standardised benchmarks, often yielding best-in-class performance. This makes them interesting both in biological models and as a useful detector in practice. We also show that keypoints can be used as a data selection step, significantly reducing the complexity in state-of-the-art object categorisation. (C) 2014 Elsevier B.V. All rights reserved.
dc.identifier.doihttps://dx.doi.org/10.1016/j.neucom.2014.09.054
dc.identifier.issn0925-2312
dc.identifier.issn1872-8286
dc.identifier.otherAUT: JRO00913; DUB00865;
dc.identifier.urihttp://hdl.handle.net/10400.1/6981
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier Science
dc.relation.isbasedonP-009-ZYS
dc.titleBIMP: A real-time biological model of multi-scale keypoint detection in V1
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceMadeira, Portugal
oaire.citation.endPage237
oaire.citation.startPage227
oaire.citation.titleNeurocomputing
oaire.citation.title6th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)
oaire.citation.volume150
person.familyNameTerzic
person.familyNameRodrigues
person.familyNamedu Buf
person.givenNameKasim
person.givenNameJoao
person.givenNameHans
person.identifier.ciencia-id8A19-98F7-9914
person.identifier.orcid0000-0001-6692-209X
person.identifier.orcid0000-0002-3562-6025
person.identifier.orcid0000-0002-4345-1237
person.identifier.ridN-6522-2013
person.identifier.ridM-5125-2013
person.identifier.scopus-author-id24544884400
person.identifier.scopus-author-id55807461600
person.identifier.scopus-author-id6604075916
rcaap.rightsopenAccess
rcaap.typearticle
relation.isAuthorOfPublication2c42d5f3-36ff-41eb-8f1a-e6cd706eab4d
relation.isAuthorOfPublication683ba85b-459c-4789-a4ff-a4e2a904b295
relation.isAuthorOfPublicationcfad5636-2c77-4db0-a3a0-d7eb97ce6bee
relation.isAuthorOfPublication.latestForDiscovery2c42d5f3-36ff-41eb-8f1a-e6cd706eab4d

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