View in EDS HTML Full Text PDF Full Text

Camera motion detection for story and multimedia information convergence.

Saved in:
Bibliographic Details
Title: Camera motion detection for story and multimedia information convergence.
Authors: Bak, Hui-Yong1 (AUTHOR), Park, Seung-Bo2 (AUTHOR) molaal@inha.ac.kr
Source: Personal & Ubiquitous Computing. Jun2023, Vol. 27 Issue 3, p1221-1231. 11p.
Subjects: Camcorders, Camera movement, Deep learning, Optical flow, Factor analysis, Cameras, Detectors
Abstract: The motion of the camera in a video effectively conveys to the viewers the intention of the director, and is an essential element that enhances their interest. Therefore, detecting the motion of the camera is a very important factor in movie analysis. Existing research to detect the motion of the camera in a video has mainly focused on pan, tilt, and zoom. However, movies use more diverse camera motions to represent complex and varied emotions. Recognizing only pan, tilt, and zoom in a movie has limitations, especially not being able to detect lateral and longitudinal movements of the camera. In this study, a method is proposed to additionally detect boom and truck as well as pan, tilt, and zoom by using deep learning technology to improve this recognition ability. Thus, this study proposes the Improved Extractor of Camera Motion along with the CNN-Based Detector. The Improved Extractor of Camera Motion uses optical flow to extract camera motion vectors from video at eight-frame intervals. The CNN-Based Detector identifies five camera motions by using ResNet-152. As a result, the performance of our proposed method shows accuracy of 86.2%. [ABSTRACT FROM AUTHOR]
Copyright of Personal & Ubiquitous Computing is the property of Springer Nature 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: 163913676
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Camera motion detection for story and multimedia information convergence.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Bak%2C+Hui-Yong%22">Bak, Hui-Yong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Park%2C+Seung-Bo%22">Park, Seung-Bo</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> molaal@inha.ac.kr</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Personal+%26+Ubiquitous+Computing%22">Personal & Ubiquitous Computing</searchLink>. Jun2023, Vol. 27 Issue 3, p1221-1231. 11p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Camcorders%22">Camcorders</searchLink><br /><searchLink fieldCode="DE" term="%22Camera+movement%22">Camera movement</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+flow%22">Optical flow</searchLink><br /><searchLink fieldCode="DE" term="%22Factor+analysis%22">Factor analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Cameras%22">Cameras</searchLink><br /><searchLink fieldCode="DE" term="%22Detectors%22">Detectors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The motion of the camera in a video effectively conveys to the viewers the intention of the director, and is an essential element that enhances their interest. Therefore, detecting the motion of the camera is a very important factor in movie analysis. Existing research to detect the motion of the camera in a video has mainly focused on pan, tilt, and zoom. However, movies use more diverse camera motions to represent complex and varied emotions. Recognizing only pan, tilt, and zoom in a movie has limitations, especially not being able to detect lateral and longitudinal movements of the camera. In this study, a method is proposed to additionally detect boom and truck as well as pan, tilt, and zoom by using deep learning technology to improve this recognition ability. Thus, this study proposes the Improved Extractor of Camera Motion along with the CNN-Based Detector. The Improved Extractor of Camera Motion uses optical flow to extract camera motion vectors from video at eight-frame intervals. The CNN-Based Detector identifies five camera motions by using ResNet-152. As a result, the performance of our proposed method shows accuracy of 86.2%. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Personal & Ubiquitous Computing is the property of Springer Nature 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=163913676
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00779-021-01585-6
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 1221
    Subjects:
      – SubjectFull: Camcorders
        Type: general
      – SubjectFull: Camera movement
        Type: general
      – SubjectFull: Deep learning
        Type: general
      – SubjectFull: Optical flow
        Type: general
      – SubjectFull: Factor analysis
        Type: general
      – SubjectFull: Cameras
        Type: general
      – SubjectFull: Detectors
        Type: general
    Titles:
      – TitleFull: Camera motion detection for story and multimedia information convergence.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Bak, Hui-Yong
      – PersonEntity:
          Name:
            NameFull: Park, Seung-Bo
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 16174909
          Numbering:
            – Type: volume
              Value: 27
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Personal & Ubiquitous Computing
              Type: main
ResultId 1