@prefix prodottidellaricerca: . @prefix istituto: . @prefix prodotto: . istituto:CDS061 prodottidellaricerca:prodotto prodotto:ID37601 . @prefix rdf: . @prefix retescientifica: . prodotto:ID37601 rdf:type retescientifica:ProdottoDellaRicerca , prodotto:TIPO1101 . @prefix rdfs: . prodotto:ID37601 rdfs:label "A feature-based model of symmetry detection. (Articolo in rivista)"@en . @prefix xsd: . @prefix pubblicazioni: . prodotto:ID37601 pubblicazioni:anno "2003-01-01T00:00:00+01:00"^^xsd:gYear . @prefix skos: . prodotto:ID37601 skos:altLabel "
Scognamillo, R., Rhodes, G., Morrone, C., & Burr, D. (2003)
A feature-based model of symmetry detection.
"^^rdf:HTML ; pubblicazioni:autori "Scognamillo, R., Rhodes, G., Morrone, C., & Burr, D."^^xsd:string ; pubblicazioni:paginaInizio "1727"^^xsd:string ; pubblicazioni:paginaFine "1733"^^xsd:string ; pubblicazioni:numeroVolume "270"^^xsd:string ; skos:note "ISI Web of Science (WOS)"^^xsd:string ; pubblicazioni:titolo "A feature-based model of symmetry detection."^^xsd:string ; prodottidellaricerca:abstract "Symmetry detection is important for many biological visual systems, including those of mammals, insects and birds. We constructed a symmetry-detection algorithm with two stages: location of the visually salient features of the image, then evaluating the symmetry of these features over a long range, by means of a simple Gaussian filter. The algorithm detects the axis of maximum symmetry for human faces (or any arbitrary image) and calculates the magnitude of the asymmetry. We have evaluated the algorithm on the dataset of Rhodes et al. (1998 Psychonom. Bull. Rev. 5, 659-669) and found that the algorithm is able to discriminate small variations of symmetry created by computer-manipulating the symmetry levels in individual faces, and that the values measured by the algorithm correlate well with human psycho-physical symmetry ratings." ; prodottidellaricerca:prodottoDi istituto:CDS061 .