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A. M. Martinez, (2002) Recognizing imprecisely localized partially occluded and expression variant faces from a single sample per class, IEEE Trans. Pattern Analysis and Machine Intelligence, 24(6), 748–763.

has been cited by the following article:

• TITLE: Unsupervised human height estimation from a single image

  AUTHORS: Ye-Peng Guan

  KEYWORDS: Human Height Estimation; Golden Proportion; Facial Proportion; Feature Extraction; Projection Model

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.2 No.6, October 27, 2009

  ABSTRACT: The single image containing only a human face not previously addressed in the literature is employed to estimate body height. The human face especially the facial vertical distribution possesses some important information which strongly correlates with the stature. The vertical proportions keep up relative constancy during the human growth. Only a few facial features such as the eyes, the lip and the chin are necessary to extract. The metric stature is estimated according to the statistical measurement sets and the facial vertical golden proportion. The estimated stature is tested with some individuals with only a single facial image. The performance of the proposed method is compared with some similar methods, which shows the proposal performs better. The experimental results highlight that the developed method estimates stature with high accuracy.