rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Video Analytics for Business Intelligence
  name:
    name part: Shan, Caifeng.
    role:
      role term: editor.
  name:
    name part: Porikli, Fatih.
    role:
      role term: editor.
  name:
    name part: Xiang, Tao.
    role:
      role term: editor.
  name:
    name part: Gong, Shaogang.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 376 p. 170 illus., 154 illus. in color. online resource.
  abstract: Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice.
  table of contents: Computational Vision -- Demographics -- Behaviour Analysis -- Systems.
  note: edited by Caifeng Shan, Fatih Porikli, Tao Xiang, Shaogang Gong.
  subject:
    topic: Engineering
  subject:
    topic: Information technology
  subject:
    topic: Business
    topic: Data processing
  subject:
    topic: Artificial intelligence
  subject:
    topic: Image processing
  subject:
    topic: Computational intelligence
  subject:
    topic: Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: IT in Business
  subject:
    topic: Image Processing and Computer Vision
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 409
  identifier: 9783642285981
  identifier: http://dx.doi.org/10.1007/978-3-642-28598-1
  record info:
    record creation date: 120404
    record change date: 20151204184121.0
    record identifier: 978-3-642-28598-1