Publication
A fast neural-dynamical approach to scale-invariant object detection
| dc.contributor.author | Terzic, Kasim | |
| dc.contributor.author | Lobato, D. | |
| dc.contributor.author | Saleiro, Mário | |
| dc.contributor.author | du Buf, J. M. H. | |
| dc.date.accessioned | 2015-11-04T12:04:40Z | |
| dc.date.available | 2015-11-04T12:04:40Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | We present a biologically-inspired method for object detection which is capable of online and one-shot learning of object appearance. We use a computationally efficient model of V1 keypoints to select object parts with the highest information content and model their surroundings by a simple binary descriptor based on responses of cortical cells. We feed these features into a dynamical neural network which binds compatible features together by employing a Bayesian criterion and a set of previously observed object views. We demonstrate the feasibility of our algorithm for cognitive robotic scenarios by evaluating detection performance on a dataset of common household items. © Springer International Publishing Switzerland 2014. | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.other | AUT: DUB00865; | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/6998 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.peerreviewed | yes | |
| dc.publisher | Springer Verlag | |
| dc.relation.isbasedon | P-00A-446 | |
| dc.title | A fast neural-dynamical approach to scale-invariant object detection | |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 518 | |
| oaire.citation.startPage | 511 | |
| oaire.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
| oaire.citation.volume | 8834 | |
| person.familyName | Terzic | |
| person.familyName | du Buf | |
| person.givenName | Kasim | |
| person.givenName | Hans | |
| person.identifier.orcid | 0000-0001-6692-209X | |
| person.identifier.orcid | 0000-0002-4345-1237 | |
| person.identifier.rid | N-6522-2013 | |
| person.identifier.rid | M-5125-2013 | |
| person.identifier.scopus-author-id | 24544884400 | |
| person.identifier.scopus-author-id | 6604075916 | |
| rcaap.rights | openAccess | |
| rcaap.type | article | |
| relation.isAuthorOfPublication | 2c42d5f3-36ff-41eb-8f1a-e6cd706eab4d | |
| relation.isAuthorOfPublication | cfad5636-2c77-4db0-a3a0-d7eb97ce6bee | |
| relation.isAuthorOfPublication.latestForDiscovery | cfad5636-2c77-4db0-a3a0-d7eb97ce6bee |
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