• DocumentCode
    2417257
  • Title

    Cross-modal identification of audiovisual streams directly from the compressed domain

  • Author

    Gruhne, M. ; Dunker, Peter ; Mikhalev, A. ; Fedotov, I. ; Andritsopoulos, F.

  • Author_Institution
    Metadata Dept., Fraunhofer IDMT, Ilmenau, Germany
  • fYear
    2009
  • fDate
    25-28 May 2009
  • Firstpage
    937
  • Lastpage
    940
  • Abstract
    During the last years, a number of search and retrieval methods for audio and visual content were described in literature. Also cross-modal approaches started to emerge recently. All search methods are based on audiovisual fingerprints, which are extracted from the audiovisual data prior to the actual search. Since the most data are available in the compressed domain, they must be decompressed prior to the feature extraction. This paper describes an audiovisual search engine, which extracts their features directly from the compressed domain, without performing a decoding algorithm. The direct video feature extraction is based on motion vectors and the direct audio feature extraction is based on a polyphase matrix description. The paper depicts an overview of the search engine, which operates cross-modal on audio, and visual features and describes the evaluation of the direct feature extraction methods in detail.
  • Keywords
    audio-visual systems; data compression; decoding; feature extraction; information retrieval; media streaming; audiovisual streaming; cross-modal identification; decoding algorithm; direct audio feature extraction; direct video feature extraction; motion vector; polyphase matrix description; retrieval methods; Content based retrieval; Data mining; Decoding; Feature extraction; Fingerprint recognition; Multimedia databases; Search engines; Streaming media; Transform coding; Video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, 2009. ISCE '09. IEEE 13th International Symposium on
  • Conference_Location
    Kyoto
  • Print_ISBN
    978-1-4244-2975-2
  • Electronic_ISBN
    978-1-4244-2976-9
  • Type

    conf

  • DOI
    10.1109/ISCE.2009.5157028
  • Filename
    5157028