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Statistical body height estimation from a single image

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2 Author(s)
Chiraz BenAbdelkader ; New York Institute of Technology, Abu Dhabi, United Arab Emirates ; Yaser Yacoob

We address the problem of estimating a person's body height from a single uncalibrated image. The novelty of our work lies in that we handle two difficult cases not previously addressed in the literature: (i) the image contains no reference length in the background scene to indicate absolute scale, (ii) the image contains the upper body part only. In a nutshell, our method combines well-known ideas from projective geometry and single-view metrology with prior probabilistic/statistical knowledge of human anthropometry, in a Bayesian-like framework. The method is demonstrated with synthetic (randomly generated) data as well as a dataset of 96 frontal images.

Published in:

Automatic Face & Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on

Date of Conference:

17-19 Sept. 2008