Content-Based Video Retrieval: An Overview

Bibtex entry :

@techreport { VG:Mar2000,
    author = { St{\'e}phane Marchand-Maillet },
    title = { Content-Based Video Retrieval: An Overview },
    institution = { CUI - University of Geneva },
    year = { 2000 },
    number = { 00.06 },
    address = { Geneva, Switzerland },
    url = { http://vision.unige.ch/publications/postscript/2000/VGTR00.06_Marchand.pdf },
    abstract = { Content-based Image Retrieval systems (CBIRS) start flourishing on the Web. Their performances are continuously improving and their base principles span a wide range of diversity. Content-based Video Retrieval systems (CBVRS) are less common and seem at a first glance to be a natural extension of CBIRS. In this document, we summarise advances made in the development of CBVRS and analyse their relationship to CBIRS. While doing so, we show that CBVRS are actually not so obvious extensions of CBIRS. (40 References) },
    url1 = { http://vision.unige.ch/publications/postscript/2000/VGTR00.06_Marchand.pdf },
    url2 = { http://viper.unige.ch/~marchand/CBVR/ },
    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