Extracting relational facts for indexing and retrieval of crime-scene photographs

This paper presents work on text-based photograph indexing and retrieval for crime investigation, an application domain where efficient querying of large crime-scene photograph databases is of crucial importance. Automating this task will change current police practices considerably, by bringing ‘intelligence’ to crime support information systems. The prototype presented, goes beyond common approaches to the automation of image indexing and retrieval, by applying a novel method that captures deep semantic relations expressed in the captions that accompany crime-scene photographs. The extraction of these semantic triples is based on advanced knowledge-based Natural Language Processing technologies and resources. q 2003 Elsevier Science B.V. All rights reserved.