Efficient access methods for content-based image retrieval with invertedfiles

Bibtex entry :

@inproceedings { VG:MSM1999c,
    author = { Henning M{\"u}ller and David McG. Squire and Wolfgang M{\"u}ller and Thierry Pun },
    title = { Efficient access methods for content-based image retrieval with invertedfiles },
    booktitle = { Multimedia Storage and Archiving Systems IV (VV02) },
    year = { 1999 },
    volume = { 3846 },
    series = { SPIE Proceedings },
    address = { Boston, Massachusetts, USA },
    month = { 20--22~September },
    keywords = { inverted file, content-based image retrieval, efficient access, searchpruning, speed evaluation },
    note = { (SPIE Symposium on Voice, Video and Data Communications) },
    url = { http://vision.unige.ch/publications/postscript/99/MuellerHSquireMuellerWPun_msasIV.ps.gz },
    abstract = { As human factor studies over the last thirty years have shown, responsetime is a very important factor for the usability of an interactivesystem, especially on the world wide web. In particular, responsetimes of under one second are often specified as a usability requirement\cite{Nie97}. This paper compares several methods for improving theevaluation time in a content-based image retrieval system (CBIRS)which uses inverted file technology. The use of the inverted filetechnology facilitates search pruning in a variety of ways, as isshown in this paper. For large databases ($> 2000$ images) and ahigh number of possible features ($> 80000$), efficient and fastaccess is necessary to allow interactive querying and browsing. Parallelaccess to the inverted file can reduce the response time. This parallelaccess is very easy to implement with little communication overhead,and thus scales well. Other search pruning methods, similar to methodsused in information retrieval, can also reduce the response timesignificantly without reducing the performance of the system. Theperformance of the system is evaluated using precision vs. recallgraphs, which are an established evaluation method in informationretrieval. A user survey was carried out in order to obtain relevancejudgments for the queries reported in this work. },
    owner = { steph },
    timestamp = { 2008.05.04 },
    url1 = { http://vision.unige.ch/publications/postscript/99/MuellerHSquireMuellerWPun_msasIV.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