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: Motion history images for action recognition and understanding
  name:
    name part: Ahad, Md. Atiqur Rahman.
    role:
      role term: creator
  name:
    name part: Ebook Library
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvi, 121 pages) : illustrations
  abstract: "Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers. The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges. Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants."--Publisher's website.
  table of contents: 1. Introduction -- Action/Activity: Nomenclature -- Atomic Actions -- Action -- Activity -- Various Dimensions of Action Recognition -- Applications -- Action Recognition is Difficult: Why? -- Some Assumptions on Action Recognition -- Action Recognition: Some Basic Steps -- Motion History Image -- 2. Action Representation -- Action Recognition -- Approaches on Bag-of-Features -- XYT: Space-Time Volume -- Spatio-Temporal Silhouettes -- Interest-Point Detectors -- Local Discriminative Approaches -- Large-Scale Features-Based Recognition -- Local Patches-Based Recognition -- Mixed Approach for Recognition -- View-Invariant Approaches -- 3. Motion History Image -- Motion History Image and its Importance -- Applications of the MHI Method/Representation -- Motion History Image: A Tutorial -- Construction of the Motion Energy Image (MEI) -- Construction of the Motion History Image (MHI) -- Importance of the MHI and the MEI -- Limitations of the MHI Method -- MHI and Its Variants: 2D/3D -- View-Based MHI and Its Variants -- View-Invariant MHI Representations -- 4 Action Datasets and MHI -- Various Datasets -- Datasets Employed in MHI -- KTH Dataset -- Weizmann Dataset -- IXMAS Dataset -- CASIA Gait Database -- Virtual Human Action Silhouette (ViHASi) Dataset -- CMU MoBo Dataset -- USF HumanID Dataset -- Marcel's Dynamic Hand Poster and Gesture Dataset -- TRECVID Dataset.
  note: Md. Atiqur Rahman Ahad.
  note: Electronic resource.
  note: Includes bibliographical references and index.
  subject:
    topic: Computer vision
  subject:
    topic: Image processing
    topic: Digital techniques
  subject:
    topic: Pattern recognition systems
  subject:
    topic: COMPUTERS / Computer Vision & Pattern Recognition
  classification: TA1634 .A43 2013eb
  classification: 006.3/7
  related item:
    title info:
      title: Motion History Images for Action Recognition and Understanding
    name:
      name part: Ahad, Md. Atiqur Rahman
    origin info:
      publisher: Dordrecht : Springer, c2011
  related item:
    title info:
      title: SpringerBriefs in computer science
  identifier: 9781447147305 (electronic bk.)
  identifier: 1447147308 (electronic bk.)
  identifier: 9781447147299
  identifier: https://ebookcentral.proquest.com/lib/tamucs/detail.action
  record info:
    record content source: EBLCP
    record creation date: 130109
    record change date: 20250816205917.6
    record identifier: in00002814524
    language of cataloging:
      language term: eng