Intelligent indexing of crime scene photographs

Pastra, Katerina; Saggion, Horacio; Wilks, Yorick

doi:10.1109/mis.2003.1179194

Cited by 10 publications

(4 citation statements)

References 6 publications

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“…The texts and images for two of the collections, the National Gallery of Art (NGA) Online Collection and the U.S. Senate Catalogue of Fine Arts, can be found online and are in the public domain. For three of the other image collections, The Vernacular Architecture Forum (VAF) 8 , The Society of Architectural Historians (SAH) 9 , and The Landscape Architecture Image Resource (LAIR) 10 , we have secured digital copies of relevant texts along with permissions for use in our testing. The final collection is the Art History Survey Collection, made available to us through ARTstor 11 .…”

Section: Discussionmentioning

confidence: 99%

“…In particular, the CLiMB Toolkit processes text associated with an image through Natural Language Processing (NLP), categorization using Machine Learning (ML), and disambiguation technologies to identify, filter, and normalize high-quality subject descriptors. Like [9] we use natural language processing techniques and domain specific ontologies, although our focus is on associated text rather than captions.…”

Section: Solutionsmentioning

confidence: 99%

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Computational Linguistics for Metadata Building (CLiMB) Text Mining for the Automatic Extraction of Subject Terms for Image Metadata

Klavans

Sidhu²,

Sheffield³

et al. 2008

Metadata Mining for Image Understanding

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In this paper, we present a fully-implemented system using computational linguistic techniques to apply automatic text mining for the extraction of metadata for image access. We describe the implementation of a workbench created for, and evaluated by, image catalogers. We discuss the current functionality and future goals for this image catalogers' toolkit, developed under the Computational Linguistics for Metadata Building (CLiMB) research project. 1 Our primary user group for initial phases of the project is the cataloger expert; in future work we address applications for end users.

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Section: Discussionmentioning

confidence: 99%

Section: Solutionsmentioning

confidence: 99%

Computational Linguistics for Metadata Building (CLiMB) Text Mining for the Automatic Extraction of Subject Terms for Image Metadata

Klavans

Sidhu²,

Sheffield³

et al. 2008

Metadata Mining for Image Understanding

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show abstract

“…The latter resulted from an experiment in a mock crime scene, where crime-scene officers used digital technology to create the multimodal documentation required when visiting a scene [50]. The objective of this analysis was the development of a text-based image-indexing algorithm, and therefore, computational applicability was of primary importance.…”

Section: The Cosmoroe Relation Frameworkmentioning

confidence: 99%

COSMOROE: a cross-media relations framework for modelling multimedia dialectics

Pastra

2008

Multimedia Systems

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Though everyday interaction is predominantly multimodal, a purpose-developed framework for describing the semantic interplay between verbal and non-verbal communication is still lacking. This lack not only indicates one's poor understanding of multimodal human behaviour, but also weakens any attempt to model such behaviour computationally. In this article, we present COSMOROE, a corpus-based framework for describing semantic interrelations between images, language and body movements. We argue that in viewing such relations from a message-formation perspective rather than a communicative goal one, one may develop a framework with descriptive power and computational applicability. We test COSMOROE for compliance to these criteria, by using it for annotating a corpus of TV travel programmes; we present all particulars of the annotation process and conclude with a discussion on the usability and scope of such annotated corpora.

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“…For each triple X-Rel-Y, the system checks whether X and Y occur as arguments in other relations and in that case rules that account for transitive and distributive properties of the semantic relations such as AND-distribution, WITH-transitivity, WITHdistribution, etc. are fired to infer new triples (Pastra et al, 2003). The idea behind an ANDdistribution rule and a "WITH" distribution rule could be expressed in the following way:…”

Section: Nlp Processesmentioning

confidence: 99%

NLP for indexing and retrieval of captioned photographs

Pastra

Saggion

Wilks

2003

Proceedings of the Tenth Conference on European Chapter of the Association for Computational Linguistics - EACL '03

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We present a text-based approach for the automatic indexing and retrieval of digital photographs taken at crime scenes. Our research prototype, SOCIS, goes beyond keyword-based approaches and methods that extract syntactic relations from captions; it relies on advanced Natural Language Processing techniques in order to extract relational facts. These relational facts consist of a "pragmatic relation" and the entities this relation connects (triples of the form: ARG1-REL-ARG2). In SOCIS, the triples are used as complex image indexing terms; however, the extraction mechanism is used not only for indexing purposes but also for image retrieval using free text queries. The retrieval mechanism computes similarity scores between querytriples and indexing-triples making use of a domain-specific ontology.

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Intelligent indexing of crime scene photographs

Cited by 10 publications

References 6 publications

Computational Linguistics for Metadata Building (CLiMB) Text Mining for the Automatic Extraction of Subject Terms for Image Metadata

Computational Linguistics for Metadata Building (CLiMB) Text Mining for the Automatic Extraction of Subject Terms for Image Metadata

COSMOROE: a cross-media relations framework for modelling multimedia dialectics

NLP for indexing and retrieval of captioned photographs

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