Boundary Preserving Dense Local Regions

We propose a dense local region detector to extract features suitable for image matching and object recognition tasks. Whereas traditional local interest operators rely on repeatable structures that often cross object boundaries (e.g., corners, scale-space blobs), our sampling strategy is driven by...

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Détails bibliographiques
Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 37(2015), 5 vom: 01. Mai, Seite 931-43
Auteur principal: Kim, Jaechul (Auteur)
Autres auteurs: Grauman, Kristen
Format: Article en ligne
Langue:English
Publié: 2015
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Journal Article Research Support, U.S. Gov't, Non-P.H.S.