Academia.edu no longer supports Internet Explorer.
To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser.
Abstract-Annotation gives more meaning to the content, explanation or annotation is sometims a necessity for multimedia content but during data transaction annotations can be lost if it is not combined with the data. For different people from different cultures, different languages and different ideas sometimes describing the same thing would be completely different.
2010 •
Abstract: With the advent of the Internet as a medium of sharing resources like text, images, audio, video, documents etc., the Web users made it a way to interchange the knowledge as well. This behavior of the Web users over the Internet phenomenally turned the WWW into a huge repository of unstructured data inducing a need of the standard based representation of the data over the Internet.
2008 •
Abstract We present a system which applies text mining using computational linguistic techniques to automatically extract, categorize, disambiguate and filter metadata for image access. Candidate subject terms are identified through standard approaches; novel semantic categorization using machine learning and disambiguation using both WordNet and a domain specific thesaurus are applied. The resulting metadata can be manually edited by image catalogers or filtered by semi-automatic rules.
Object and scene recognition is widely recognized as a difficult problem in computer vision. We present here an approach to this problem that merges recognition of an object and its background. Relying on the assumption that given objects are strongly linked to given background scenes (a deer is more likely to appear in a forest than on an iceberg), we learn object classifiers using joint estimations of object and scene. Such an approach would normally require a large quantity of training images labelled with object/background scene associations. To circumvent costly manual training set labelling, we propose a cross-modal approach, learning and incorporating contextual information via automatic text analysis from theWeb, to generate the conditional probabilities of an object given a background scene. This method allows us to strictly distinguish the object classifier from the background scene classifier, and then merge them using estimated conditional probabilities through a learned Bayesian network. The key contribution of this paper is a framework that provides a unified, multimodal approach to learning and using contextual information for improving image processing using statistics obtained from processing Web text
Multimedia Tools and Applications
Computational linguistics for metadata building (CLiMB): using text mining for the automatic identification, categorization, and disambiguation of subject terms for image metadata2009 •
Words can be associated with images in different ways. Google and Yahoo use text found around a photo on a web page, Flickr image uploaders add their own tags. How do the annotations differ when they are extracted from text and when they are manually created? How does these language populations compare to written text? Here we continue our exploration of the differences in these languages.
OntoImage 2006 Workshop on Language Resources …
Image-Language Association: are we looking at the right features?2007 •
Personalized Access to Cultural Heritage PATCH 2008
Semantics-driven recommendations in cross-media museum applications2008 •
Abstract. In this paper we present the CHIP demonstrator aimed at helping users to explore the Rijksmuseum Amsterdam collection both online and inside the museum. Cultural heritage data from various external sources is integrated to provide an enriched semantic knowledge structure. The resulting RDF/OWL graph is the basis for CHIP main functionality for recommendations, search and personalized interaction.
2008 •
The goal of this Workpackage is to develop services that facilitate learners and tutors in accessing formal and informal knowledge sources in the context of a learning task. More specifically, we will support the learner through a personalized search. A Common Semantic Framework will be developed which will provide recommendations on the basis of the user profile, his interests, his preferences, his network and obviously the learning task.
Multimedia Tools and Applications
Interactive Multi-user Video Retrieval Systems2012 •
2006 •
International Journal of Computer Applications Technology and Research
Semantic Annotation: The Mainstay of Semantic Web2013 •
International Journal of Metadata, Semantics and Ontologies
A hybrid ontology and visual-based retrieval model for cultural heritage multimedia collections2008 •
Springer Journal of Intelligent Information Systems (JIIS)
Image Understanding and the Web : a State-of-the-Art Review2014 •
Proceedings of the 6th International Conference on Advances in Mobile Computing and Multimedia - MoMM '08
Semantic keyword-based retrieval of photos taken with mobile devices2008 •
Lecture Notes in Computer Science
A Semantic Approach and a Web Tool for Contextual Annotation of Photos Using Camera Phones2007 •
Electronic Library, The
Semantic annotation and retrieval of documentary media objects2012 •
2008 •
Arxiv preprint cs/0110026
Information retrieval in current research information systems2001 •
Proceedings of the …
Integration of semantic, metadata and image search engines with a text search engine for patent retrieval2008 •
2004 •
Foundations and Trends® in Information Retrieval
Concept-Based Video Retrieval2007 •
… Review on Computers and Software (I …
Semantic Web: A state of the art survey2007 •
Lecture Notes in Computer Science
PhotoMap – Automatic Spatiotemporal Annotation for Mobile Photos2007 •
Journal of Location Based Services
PhotoMap: from location and time to context-aware photo annotations2008 •
International Journal of Learning Technology
Multimedia analysis techniques for e-learning2012 •
2009 •
… for Digital Humanities …
A framework for improved access to museum databases in the semantic web2011 •
Procedia Computer Science
A Distributed System for Multimedia Monitoring, Publishing and Retrieval2014 •
International Journal of Web Engineering and Technology
Technically approaching the semantic web bottleneck2010 •
Cases and Applications
Semantic Web Take-Off in a European Industry Perspective2009 •