Estimating average growth trajectories in shape-space using kernel smoothing

被引：105

作者：

Hutton, TJ

Buxton, BF

Hammond, P

Potts, HWW

机构：

[1] UCL, Eastman Dent Inst Oral Hlth Care Sci, London WC1X 8LD, England

[2] UCL, Dept Comp Sci, London WC1E 6BT, England

[3] UCL, Eastman Dent Inst Oral Hlth Care Sci, Biomed Informat Unit, London WC1X 8LD, England

[4] St Thomas Hosp, Adamson Ctr Mental Hlth, Guys Kings & St Thomas Sch Med, Canc Res UK London Psychosocial Grp, London SE1 7EH, England

来源：

IEEE TRANSACTIONS ON MEDICAL IMAGING | 2003年 / 22卷 / 06期

关键词：

deformable models; facial growth; medical image registration; morphometrics;

D O I：

10.1109/TMI.2003.814784

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we show how a dense surface point distribution model of the human face can be computed and demonstrate the usefulness of the high-dimensional shape-space for expressing the shape changes associated with growth and aging. We show how average growth trajectories for the human face can be computed in the absence of longitudinal data by using kernel smoothing across a population. A training set of three-dimensional surface scans of 199 male and 201 female subjects of between 0 and 50 years of age is used to build the model.

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页码：747 / 753

页数：7