View in EDS HTML Full Text PDF Full Text

Comprehensible Video Thumbnails.

Saved in:
Bibliographic Details
Title: Comprehensible Video Thumbnails.
Authors: Kim, Jongdae1, Gray, Charles1, Asente, Paul2, Collomosse, John1
Source: Computer Graphics Forum. May2015, Vol. 34 Issue 2, p167-177. 11p. 2 Color Photographs, 6 Diagrams, 1 Chart, 3 Graphs.
Subjects: Thumbnail images (Image processing), Motion analysis, Cluster analysis (Statistics), Stochastic analysis, Optical flow
Abstract: We present the Comprehensible Video Thumbnail; an automatically generated visual précis that summarizes salient objects and their dynamics within a video clip. Salient moving objects are detected within clips using a novel stochastic sampling technique that identifies, clusters and then tracks regions exhibiting affine motion coherence within the clip. Tracks are analyzed to determine salient instants at which motion and/or appearance changes significantly, and the resulting objects arranged in a stylized composition optimized to reduce visual clutter and enhance understanding of scene content through classification and depiction of motion type and trajectory. The result is an object-level visual gist of the clip, obtained with full automation and depicting content and motion with greater descriptive power that prior approaches. We demonstrate these benefits through a user study in which the comprehension of our video thumbnails is compared to the state of the art over a wide variety of sports footage. [ABSTRACT FROM AUTHOR]
Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 108645048
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comprehensible Video Thumbnails.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kim%2C+Jongdae%22">Kim, Jongdae</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Gray%2C+Charles%22">Gray, Charles</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Asente%2C+Paul%22">Asente, Paul</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Collomosse%2C+John%22">Collomosse, John</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Computer+Graphics+Forum%22">Computer Graphics Forum</searchLink>. May2015, Vol. 34 Issue 2, p167-177. 11p. 2 Color Photographs, 6 Diagrams, 1 Chart, 3 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Thumbnail+images+%28Image+processing%29%22">Thumbnail images (Image processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Motion+analysis%22">Motion analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+analysis%22">Stochastic analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+flow%22">Optical flow</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We present the Comprehensible Video Thumbnail; an automatically generated visual précis that summarizes salient objects and their dynamics within a video clip. Salient moving objects are detected within clips using a novel stochastic sampling technique that identifies, clusters and then tracks regions exhibiting affine motion coherence within the clip. Tracks are analyzed to determine salient instants at which motion and/or appearance changes significantly, and the resulting objects arranged in a stylized composition optimized to reduce visual clutter and enhance understanding of scene content through classification and depiction of motion type and trajectory. The result is an object-level visual gist of the clip, obtained with full automation and depicting content and motion with greater descriptive power that prior approaches. We demonstrate these benefits through a user study in which the comprehension of our video thumbnails is compared to the state of the art over a wide variety of sports footage. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computer Graphics Forum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=108645048
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1111/cgf.12550
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 167
    Subjects:
      – SubjectFull: Thumbnail images (Image processing)
        Type: general
      – SubjectFull: Motion analysis
        Type: general
      – SubjectFull: Cluster analysis (Statistics)
        Type: general
      – SubjectFull: Stochastic analysis
        Type: general
      – SubjectFull: Optical flow
        Type: general
    Titles:
      – TitleFull: Comprehensible Video Thumbnails.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kim, Jongdae
      – PersonEntity:
          Name:
            NameFull: Gray, Charles
      – PersonEntity:
          Name:
            NameFull: Asente, Paul
      – PersonEntity:
          Name:
            NameFull: Collomosse, John
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2015
              Type: published
              Y: 2015
          Identifiers:
            – Type: issn-print
              Value: 01677055
          Numbering:
            – Type: volume
              Value: 34
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Computer Graphics Forum
              Type: main
ResultId 1