3D face tracking for infant monitoring using dense HOG and drift reduction

R.W.J.J. Saeijs, W.E. Tjon A Ten, P.H.N. de With

Onderzoeksoutput: Bijdrage aan congresPaperAcademic

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Samenvatting

This paper presents a new algorithm for 3D face tracking intended for clinical infant pain monitoring. The algorithm uses a cylinder head model and 3D head pose recovery by alignment of dynamically extracted templates based on dense-HOG features. Drift reduction is obtained from re-registration in combination with multi-pose state estimation by a square-root unscented Kalman filter. Results on videos of moving infants in hospital show good tracking for poses up to 50 degrees from upright-frontal, with mean eyelocation error relative to inter-ocular distance below 9%.
Originele taal-2Engels
Pagina's1-2
StatusGepubliceerd - 2016
EvenementNCCV 2016: the Netherlands Conference on Computer Vision - Lunteren, Nederland
Duur: 12 dec 201613 dec 2016
http://http://www.nccv16.nl

Congres

CongresNCCV 2016: the Netherlands Conference on Computer Vision
Verkorte titelNCCV2016
LandNederland
StadLunteren
Periode12/12/1613/12/16
Internet adres

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  • Citeer dit

    Saeijs, R. W. J. J., Tjon A Ten, W. E., & de With, P. H. N. (2016). 3D face tracking for infant monitoring using dense HOG and drift reduction. 1-2. Paper gepresenteerd op NCCV 2016: the Netherlands Conference on Computer Vision, Lunteren, Nederland.