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: Visual Content Indexing and Retrieval with Psycho-Visual Models
  name:
    name part: Benois-Pineau, Jenny.
    role:
      role term: editor.
  name:
    name part: Le Callet, Patrick.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 267 p. 105 illus., 81 illus. in color. online resource.
  abstract: This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval. The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book. This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.
  table of contents: Visual content indexing and retrieval with psycho-visual models -- Perceptual Texture Similarity for Machine Intelligence Applications -- Deep Saliency: Prediction of Interestingness In Video With CNN -- Introducing Image Saliency Information Into Content Based Indexing And Emotional Impact Analysis -- Saliency Prediction for Action Recognition -- Querying Multiple Simultaneous Video Streams with 3D Interest Maps -- Information theoretical model for saliency prediction. Application to Attentive CBIR -- Image retrieval based on query by saliency content -- Visual Saliency for the Visualization of Digital Paintings -- Predicting Interestingness of Visual Content -- Glossary.
  note: edited by Jenny Benois-Pineau, Patrick Le Callet.
  subject:
    topic: Computer science
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Multimedia information systems
  subject:
    topic: Artificial intelligence
  subject:
    topic: Image processing
  subject:
    topic: Computer Science
  subject:
    topic: Image Processing and Computer Vision
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Multimedia Information Systems
  classification: TA1637-1638
  classification: TA1634
  classification: 006.6
  classification: 006.37
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Multimedia Systems and Applications
  identifier: 9783319576879
  identifier: http://dx.doi.org/10.1007/978-3-319-57687-9
  record info:
    record creation date: 171015
    record change date: 20171015132739.0
    record identifier: 978-3-319-57687-9