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: Principles of Visual Information Retrieval
  name:
    name part: Lew, Michael S.
    role:
      role term: creator
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: xxk
    date issued: 2001
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (xix, 356 pages)
  abstract: Principles of Visual Information Retrieval introduces the basic concepts and techniques in VIR and develops a foundation that can be used for further research and study. Divided into 2 parts, the first part describes the fundamental principles. A chapter is devoted to each of the main features of VIR, such as colour, texture and shape-based search. There is coverage of search techniques for time-based image sequences or videos, and an overview of how to combine all the basic features described and integrate context into the search process. The second part looks at advanced topics such as multimedia query, specification, visual learning and semantics, and offers state-of-the-art coverage that is not available in any other book on the market. This book will be essential reading for researchers in VIR, and for final year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, Computer Vision and Pattern Recognition.
  table of contents: Part I: Fundamental Principles: Visual Information Retrieval: Paradigms, Applications and Research Issues. Color Based Retrieval. Texture Features for Content Based Retrieval. State of the Art in Shape Matching. Feature Similarity. Feature Selection and Visual Learning. Video Indexing and Understanding -- Part II: Advanced Topics: Query Languages for Multimedia Search. Relevance Feedback Techniques in Image Retrieval. Mix and Match Features in the ImageRover Search Engine. Integrating Analysis of Context and Image Content. Semantic Based Retrieval of Visual Data. Trademark Image Retrieval -- Author Index -- Subject Index.
  note: edited by Michael S. Lew.
  note: Electronic resource.
  subject:
    topic: Computer science
  subject:
    topic: Information storage and retrieval systems
  subject:
    topic: Multimedia systems
  subject:
    topic: Artificial intelligence
  subject:
    topic: Optical pattern recognition
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer science
  subject:
    topic: Information storage and retrieval systems
  subject:
    topic: Multimedia systems
  subject:
    topic: Optical pattern recognition
  classification: Q337.5
  classification: TK7882.P3
  classification: 006.4
  related item:
    title info:
      title: Advances in pattern recognition
  identifier: 9781447137023 (electronic bk.)
  identifier: 1447137027 (electronic bk.)
  identifier: 9781849968683
  identifier: 1849968683
  identifier: 1447137027
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: AU@
    record creation date: 130220
    record change date: 20260422155645.6
    record identifier: in00003569371
    language of cataloging:
      language term: eng