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Probabilistic Retrieval with a Visual Grammar Selim Aksoy, Giovanni Marchisio, Krzysztof Koperski, Carsten Tusk
 

Summary: Probabilistic Retrieval with a Visual Grammar
Selim Aksoy, Giovanni Marchisio, Krzysztof Koperski, Carsten Tusk
Insightful Corporation
1700 Westlake Ave. N., Suite 500
Seattle, WA, 98109-3044
{saksoy,giovanni,krisk,ctusk}@insightful.com
Abstract--We describe a system for content-based retrieval and classifi-
cation of multispectral images. Our system models images on pixel, region
and scene levels. To reduce the gap between low-level features and high-
level user semantics, and to support complex query scenarios that consist
of many regions with different feature characteristics, we propose a prob-
abilistic visual grammar that includes automatic identification of region
prototypes and modeling of their spatial relationships. A Bayesian frame-
work is used to automatically classify scenes based on these models. We
demonstrate our system with query scenarios that cannot be expressed by
traditional region or scene level approaches but where the visual grammar
provides accurate classifications and effective retrieval.
I. INTRODUCTION
Automatic content extraction, classification and retrieval are
highly desired goals in intelligent remote sensing databases.

  

Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University

 

Collections: Computer Technologies and Information Sciences