Surface Regions of Interest for Viewpoint Selection

While the detection of the interesting regions in images has been extensively studied, relatively few papers have addressed surfaces. This paper proposes an algorithm for detecting the regions of interest of surfaces. It looks for regions that are distinct both locally and globally and accounts for...

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Détails bibliographiques
Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 38(2016), 12 vom: 01. Dez., Seite 2544-2556
Auteur principal: Leifman, George (Auteur)
Autres auteurs: Shtrom, Elizabeth, Tal, Ayellet
Format: Article en ligne
Langue:English
Publié: 2016
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Journal Article
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520 |a While the detection of the interesting regions in images has been extensively studied, relatively few papers have addressed surfaces. This paper proposes an algorithm for detecting the regions of interest of surfaces. It looks for regions that are distinct both locally and globally and accounts for the distance to the foci of attention. It is also shown how this algorithm can be adopted to saliency detection in point clouds. Many applications can utilize these regions. In this paper we explore one such application-viewpoint selection. The most informative views are those that collectively provide the most descriptive presentation of the surface. We show that our results compete favorably with the state-of-the-art results 
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