{MRML}: A Communication Protocol for Content-Based Image Retrieval

Bibtex entry :

@inproceedings { VG:MMM2000a,
    author = { Wolfgang M{\"u}ller and Henning M{\"u}ller and St{\'e}phane Marchand-Maillet and Thierry Pun and David McG. Squire and Zoran Pe\u{c}enovi\'{c} and Christoph Giess and Arjen P. de Vries },
    title = { {MRML}: A Communication Protocol for Content-Based Image Retrieval },
    booktitle = { International Conference on Visual Information Systems (Visual 2000) },
    year = { 2000 },
    address = { Lyon, France },
    month = { nov 2--4 },
    url = { http://vision.unige.ch/publications/postscript/2000/MuellerWMuellerHMarchandPunSquireGiessVries_visual2000.ps.gz },
    abstract = { In this paper we introduce and describe the Multimedia Retrieval MarkupLanguage (MRML). This XML-based markup language is the basis foran open communication protocol for content-based image retrievalsystems (CBIRSs). MRML was initially designed as a means of separatingCBIR engines from their user interfaces. It is, however, also extensibleas the basis for standardised performance evaluation procedures.Such a tool is essential for the formulation and implementation ofcommon benchmarks for CBIR. A common protocol can also bring newdynamics to the CBIR field --- it makes the development of new systemsfaster and more efficient, and opens the door of the CBIR researchfield to other disciplines such as Human-Computer Interaction. TheMRML specifications, as well as the first MRML-compliant applications,are freely available and are introduced in this paper. },
    owner = { steph },
    timestamp = { 2008.05.04 },
    url1 = { http://vision.unige.ch/publications/postscript/2000/MuellerWMuellerHMarchandPunSquireGiessVries_visual2000.pdf },
    vgclass = { refpap },
    vgproject = { viper },

Keywords: machine learning, information geometry, data mining, Big Data, affective information retrieval (recherche d'information), information visualisation, content-based image and video retrieval (CBIR, CBR, CBVR, CBMR, CBMIR), information mining, classification, multimedia and multimodal information management, semantic web, knowledge base (RDF, OWL, XML, metadata, auto-annotation, description), multimodal information fusion