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

Bibtex entry :

@techreport { VG:MMM2000,
    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 },
    institution = { Computer Vision Group, Computing Centre, University of Geneva },
    year = { 2000 },
    number = { 00.02 },
    address = { rue G\'en\'eral Dufour, 24, CH-1211 Gen\`eve, Switzerland },
    month = { mar },
    url = { http://vision.unige.ch/publications/postscript/2000/VGTR00.02_MuellerWMuellerHMarchandPunSquireGiessVries.ps.gz },
    abstract = { In this paper we introduce and describe the Multimedia Retrieval Markup Language (MRML). This XML-based markup language is the basis for an open communication protocol for content-based image retrieval systems (CBIRSs). MRML was initially designed as a means of separating CBIR engines from their user interfaces. It is, however, also extensible as the basis for standardized performance evaluation procedures. Such a tool is essential for the formulation and implementation of common benchmarks for CBIR. A common protocol can also bring new dynamics to the CBIR field---it makes the development of new systems faster and more efficient, and opens the door of the CBIR research field to other disciplines such as Human-Computer Interaction. The MRML specifications, as well as the first MRML-compliant applications, are freely available and are introduced in this paper. },
    url1 = { http://vision.unige.ch/publications/postscript/2000/VGTR00.02_MuellerWMuellerHMarchandPunSquireGiessVries.pdf },
    vgclass = { report },
    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