Audio Surveillance

DOI Web Site Web Site 被引用文献4件
  • Marco Crocco
    Pattern Analysis and Computer Vision, Istituto Italiano di Tecnologia, Genova, Italy
  • Marco Cristani
    University of Verona, Verona, Italy
  • Andrea Trucco
    University of Genova, Genova, Italy
  • Vittorio Murino
    Pattern Analysis and Computer Vision, Istituto Italiano di Tecnologia - University of Verona, Genova, Italy

書誌事項

タイトル別名
  • A Systematic Review
公開日
2016-02-22
権利情報
  • https://www.acm.org/publications/policies/copyright_policy#Background
DOI
  • 10.1145/2871183
公開者
Association for Computing Machinery (ACM)

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説明

<jats:p>Despite surveillance systems becoming increasingly ubiquitous in our living environment, automated surveillance, currently based on video sensory modality and machine intelligence, lacks most of the time the robustness and reliability required in several real applications. To tackle this issue, audio sensory devices have been incorporated, both alone or in combination with video, giving birth in the past decade, to a considerable amount of research. In this article, audio-based automated surveillance methods are organized into a comprehensive survey: A general taxonomy, inspired by the more widespread video surveillance field, is proposed to systematically describe the methods covering background subtraction, event classification, object tracking, and situation analysis. For each of these tasks, all the significant works are reviewed, detailing their pros and cons and the context for which they have been proposed. Moreover, a specific section is devoted to audio features, discussing their expressiveness and their employment in the above-described tasks. Differing from other surveys on audio processing and analysis, the present one is specifically targeted to automated surveillance, highlighting the target applications of each described method and providing the reader with a systematic and schematic view useful for retrieving the most suited algorithms for each specific requirement.</jats:p>

収録刊行物

  • ACM Computing Surveys

    ACM Computing Surveys 48 (4), 1-46, 2016-02-22

    Association for Computing Machinery (ACM)

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