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Medientyp:
E-Artikel;
Sonstige Veröffentlichung
Titel:
Integration of prior knowledge into dense image matching for video surveillance
Beteiligte:
Menze, Moritz
[VerfasserIn];
Heipke, Christian
[VerfasserIn];
Paparoditis, N.
[VerfasserIn];
Schindler, K.
[VerfasserIn]
Erschienen:
Göttingen : Copernicus GmbH, 2014
Erschienen in:ISPRS Technical Commission III Symposium : 5 – 7 September 2014, Zurich, Switzerland ; The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XL-3
Anmerkungen:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Beschreibung:
Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more challenging camera configurations. In the context of video surveillance the typically large spatial extent of the region of interest and repetitive structures in the scene render the application of dense image matching a challenging task. In this paper we present an approach that derives strong prior knowledge from a planar approximation of the scene. This information is integrated into a graph-cut based image matching framework that treats the assignment of optimal disparity values as a labelling task. Introducing the planar prior heavily reduces ambiguities together with the search space and increases computational efficiency. The results provide a proof of concept of the proposed approach. It allows the reconstruction of dense point clouds in more general surveillance camera setups with wider stereo baselines. ; BMBF/13N10809 ; BMBF/13N10810 ; BMBF/13N10811 ; BMBF/13N10812 ; BMBF/13N10813 ; BMBF/13N10814