Segmentation and classification of objects with implicit scene context

Authors:
Jan D. Wegner;Bodo Rosenhahn;Uwe Sörgel
Affiliations:
Institute of Photogrammetry and GeoInformation, Germany;Institut für Informationsverarbeitung, Leibniz Universität Hannover, Germany;Institute of Photogrammetry and GeoInformation, Germany
Venue:
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
Year:
2011

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Abstract

We present a novel approach to segment and classify objects in images into two classes. A binary conditional random field (CRF) framework is augmented with an unsupervised clustering step learning contextual relations of objects, the so-called implicit scene context (ISC). Several experiments with simulated data, images from benchmark data sets, and aerial images of an urban area show improved results compared to a standard CRF.