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DocMIR: An automatic document-based indexing system for meeting retrieval

Behera, Ardhendu ; Lalanne, Denis ; Ingold, Rolf

In: Multimedia Tools and Applications, 2008, vol. 37, no. 2, p. 135-167

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    Title
    • DocMIR: An automatic document-based indexing system for meeting retrieval
    Author
    • Behera, Ardhendu. Department of Informatics, University of Fribourg, Bd de Perolles 90, CH-1700, Fribourg, Switzerland
    • Lalanne, Denis. Department of Informatics, University of Fribourg, Bd de Perolles 90, CH-1700, Fribourg, Switzerland
    • Ingold, Rolf. Department of Informatics, University of Fribourg, Bd de Perolles 90, CH-1700, Fribourg, Switzerland
    Document Type
    • Postprint
    Language
    • English
    Published in
    • Multimedia Tools and Applications, 2008, vol. 37, no. 2, p. 135-167. Springer US; http://www.springer-ny.com
    Other Version
    OAI-PMH Identifier
    • oai:doc.rero.ch:321873
    Summary
    This paper describes the DocMIR system which captures, analyzes and indexes automatically meetings, conferences, lectures, etc. by taking advantage of the documents projected (e.g. slideshows, budget tables, figures, etc.) during the events. For instance, the system can automatically apply the above-mentioned procedures to a lecture and automatically index the event according to the presented slides and their contents. For indexing, the system requires neither specific software installed on the presenter's computer nor any conscious intervention of the speaker throughout the presentation. The only material required by the system is the electronic presentation file of the speaker. Even if not provided, the system would temporally segment the presentation and offer a simple storyboard-like browsing interface. The system runs on several capture boxes connected to cameras and microphones that records events, synchronously. Once the recording is over, indexing is automatically performed by analyzing the content of the captured video containing projected documents and detects the scene changes, identifies the documents, computes their duration and extracts their textual content. Each of the captured images is identified from a repository containing all original electronic documents, captured audio-visual data and metadata created during post-production. The identification is based on documents' signatures, which hierarchically structure features from both layout structure and color distributions of the document images. Video segments are finally enriched with textual content of the identified original documents, which further facilitate the query and retrieval without using OCR. The signature-based indexing method proposed in this article is robust and works with low-resolution images and can be applied to several other applications including real-time document recognition, multimedia IR and augmented reality systems