Grouping of Semantically Similar Image Positions

Authors:
Lutz Priese;Frank Schmitt;Nils Hering
Affiliations:
Institute for Computational Visualistics, University Koblenz-Landau, Koblenz,;Institute for Computational Visualistics, University Koblenz-Landau, Koblenz,;Institute for Computational Visualistics, University Koblenz-Landau, Koblenz,
Venue:
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Year:
2009

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Abstract

Features from the Scale Invariant Feature Transformation (SIFT) are widely used for matching between spatially or temporally displaced images. Recently a topology on the SIFT features of a single image has been introduced where features of a similar semantics are close in this topology. We continue this work and present a technique to automatically detect groups of SIFT positions in a single image where all points of one group possess a similar semantics. The proposed method borrows ideas and techniques from the Color-Structure-Code segmentation method and does not require any user intervention.