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https://hdl.handle.net/10216/6858Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Maria João M. Vasconcelos | |
| dc.creator | João Manuel R. S. Tavares | |
| dc.date.accessioned | 2022-09-16T09:54:18Z | - |
| dc.date.available | 2022-09-16T09:54:18Z | - |
| dc.date.issued | 2008 | |
| dc.identifier.issn | 1526-1492 | |
| dc.identifier.other | sigarra:57860 | |
| dc.identifier.uri | https://hdl.handle.net/10216/6858 | - |
| dc.description.abstract | In this work we developed methods to automatically extract significant points of objects like hand palms and faces represented in images that can be used to build Point Distribution Models automatically. These models are further used to segment the modelled objects in new images, through the use of Active Shape Models or Active Appearance Models. These models showed to be efficient in the segmentation of objects, but had as drawback the fact that the labelling of the landmark points was usually manually made and consequently time consuming. Thus, in this paper we describe some methods capable to extract significant points of objects like hand palms and compare the segmentation results in new images. | |
| dc.language.iso | eng | |
| dc.rights | openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Processamento de imagem, Outras ciências da engenharia e tecnologias | |
| dc.subject | Image processing, Other engineering and technologies | |
| dc.title | Methods to automatically build Point Distribution Models for objects like hand palms and faces represented in images | |
| dc.type | Artigo em Revista Científica Internacional | |
| dc.contributor.uporto | Faculdade de Engenharia | |
| dc.identifier.doi | 10.3970/cmes.2008.036.213 | |
| dc.subject.fos | Ciências da engenharia e tecnologias::Outras ciências da engenharia e tecnologias | |
| dc.subject.fos | Engineering and technology::Other engineering and technologies | |
| Appears in Collections: | FEUP - Artigo em Revista Científica Internacional | |
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