Applying distance histograms for robust object recognition
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Campo DC | Valor | Idioma |
---|---|---|
dc.contributor | Informática Industrial e Inteligencia Artificial | en |
dc.contributor | Informática Industrial y Redes de Computadores | en |
dc.contributor.author | Arques Corrales, Pilar | - |
dc.contributor.author | Pujol, Francisco A. | - |
dc.contributor.author | Llorens Largo, Faraón | - |
dc.contributor.author | Pujol, Mar | - |
dc.contributor.author | Rizo, Ramón | - |
dc.contributor.other | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | en |
dc.contributor.other | Universidad de Alicante. Departamento de Tecnología Informática y Computación | en |
dc.date.accessioned | 2007-05-10T14:16:36Z | - |
dc.date.available | 2007-05-10T14:16:36Z | - |
dc.date.issued | 2007-01 | - |
dc.identifier.citation | ARQUES CORRALES, Pilar, et al. “Applying distance histograms for robust object recognition”. Kybernetes. 2007, Vol. 36, No. 1. ISSN 0368-492X, pp. 42-51 | en |
dc.identifier.issn | 0368-492X | - |
dc.identifier.uri | http://hdl.handle.net/10045/660 | - |
dc.description.abstract | One of the main goals of vision systems is to recognize objects in real world to perform appropriate actions. This implies the ability of handling objects and, moreover, to know the relations between these objects and their environment in what we call scenes. Most of the time, navigation in unknown environments is difficult due to a lack of easily identifiable landmarks. Hence, in this work, some geometric features to identify objects are considered. Firstly, a Markov random field segmentation approach is implemented. Then, the key factor for the recognition is the calculation of the so-called distance histograms, which relate the distances between the border points to the mass center for each object in a scene. | en |
dc.description.sponsorship | This work has been supported by the Conselleria d’Empresa, Universitat i Ciència, of the Generalitat Valenciana, project number GV04B685. | en |
dc.language | eng | en |
dc.publisher | Emerald Group Publishing Limited | en |
dc.subject | Cybernetics | en |
dc.subject | Image processing | en |
dc.subject | Markov processes | en |
dc.subject.other | Ciencia de la Computación e Inteligencia Artificial | en |
dc.title | Applying distance histograms for robust object recognition | en |
dc.type | info:eu-repo/semantics/article | en |
dc.peerreviewed | si | en |
dc.identifier.doi | 10.1108/03684920710741134 | - |
dc.relation.publisherversion | http://dx.doi.org/10.1108/03684920710741134 | - |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | - |
Aparece en las colecciones: | INV - i3a - Artículos de Revistas INV - Smart Learning - Artículos de Revistas |
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Kybernetes_Enero_2007.pdf | Versión final (acceso restringido) | 209,72 kB | Adobe PDF | Abrir Solicitar una copia |
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