Video analysis of Hammersmith lateral tilting examination using Kalman filter guided multi-path tracking.

Video object tracking plays an important role in many computer vision-aided applications. This paper presents a novel multi-path analysis-based video object tracking algorithm. Trajectory of the moving object is refined using a Kalman filter-based prediction method. The proposed algorithm has been u...

Descripción completa

Detalles Bibliográficos
Publicado en:Medical & Biological Engineering & Computing Vol. 52; no. 9; pp. 759 - 773
Autores principales: Dogra, Debi Prosad, Badri, Vishal, Majumdar, Arun Kumar, Sural, Shamik, Mukherjee, Jayanta, Mukherjee, Suchandra, Singh, Arun
Formato: research Journal Article
Publicado: Springer Nature Sep2014
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103840781&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 103840781
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        01400118
        PO0
      jtl: Medical & Biological Engineering & Computing
      issn: 01400118
      maglogo: N
    pubinfo:
      dt: Sep2014
      vid: 52
      iid: 9
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        103840781
        NLM25096789
        2012689108
        10.1007/s11517-014-1178-2
        NLM25096789
        103840781
      ppf: 759
      ppct: 14
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Video analysis of Hammersmith lateral tilting examination using Kalman filter guided multi-path tracking.
      aug:
        au:
          Dogra, Debi Prosad
          Badri, Vishal
          Majumdar, Arun Kumar
          Sural, Shamik
          Mukherjee, Jayanta
          Mukherjee, Suchandra
          Singh, Arun
        affil: School of Electrical Sciences, IIT Bhubaneswar, Bhubaneswar, 751013, India, dpdogra@iitbbs.ac.in.
      sug:
        subj:
          Image Processing, Computer Assisted Methods
          Videorecording
          Algorithms
          Computer Simulation
          Human
          Infant
          Models, Biological
          Sensitivity and Specificity
          Infant: 1-23 months
      ab: Video object tracking plays an important role in many computer vision-aided applications. This paper presents a novel multi-path analysis-based video object tracking algorithm. Trajectory of the moving object is refined using a Kalman filter-based prediction method. The proposed algorithm has been used successfully to analyze one of the complex infant neurological examinations often referred to as Hammersmith lateral tilting test. This is an important test of the infant neurological assessment process, and this test is difficult to grade by visual observation. It has been shown in this paper that the proposed video object tracking algorithm can be used to analyze the videos of fast moving objects by incorporating application-specific information. For example, the proposed tracking algorithm can be used to assess lateral tilting test of the Hammersmith infant neurological examinations. The algorithm has been tested with several video recordings of this test which were captured at the neurodevelopment clinic of the SSKM Hospital, Kolkata, India during the period of the study. It is found that the proposed algorithm is capable of estimating the score for the test with high values of sensitivity and specificity.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N