Yoon, Sang Min ; Graf, Holger ; Kuijper, Arjan (2014)
Hierarchical Image Representation using 3D Camera Geometry for Content-based Image Retrieval.
In: Engineering Applications of Artificial Intelligence, 30
doi: 10.1016/j.engappai.2014.01.012
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
In this paper we present a hierarchical image representation methodology by clustering images with 3D camera geometry in order to efficiently retrieve the images according to user's viewpoint. The framework of our proposed technique is composed of two steps: first the visual correlation analysis between images in a large database is determined by the estimated 3D camera geometry and second images are classified using a constrained agglomerative hierarchical image clustering method to retrieve the images the users search. The constrained agglomerative hierarchical image clustering method provides balanced hierarchical layers, independent of the number of images within the cluster. It also provides a convenient way to browsing, navigating, and categorizing of the images with various viewpoints, illumination, and partial occlusion.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2014 |
| Autor(en): | Yoon, Sang Min ; Graf, Holger ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Hierarchical Image Representation using 3D Camera Geometry for Content-based Image Retrieval |
| Sprache: | Englisch |
| Publikationsjahr: | 2014 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Engineering Applications of Artificial Intelligence |
| Jahrgang/Volume einer Zeitschrift: | 30 |
| DOI: | 10.1016/j.engappai.2014.01.012 |
| Kurzbeschreibung (Abstract): | In this paper we present a hierarchical image representation methodology by clustering images with 3D camera geometry in order to efficiently retrieve the images according to user's viewpoint. The framework of our proposed technique is composed of two steps: first the visual correlation analysis between images in a large database is determined by the estimated 3D camera geometry and second images are classified using a constrained agglomerative hierarchical image clustering method to retrieve the images the users search. The constrained agglomerative hierarchical image clustering method provides balanced hierarchical layers, independent of the number of images within the cluster. It also provides a convenient way to browsing, navigating, and categorizing of the images with various viewpoints, illumination, and partial occlusion. |
| Freie Schlagworte: | Business Field: Digital society, Research Area: Computer vision (CV), Image retrieval, Image clustering, 3D cameras, Geometry |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 12 Nov 2018 11:16 |
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