Estimating anthropometry and pose from a single image

Carlos Barron, Ioannis A. Kakadiaris

Research output: Contribution to journalConference articlepeer-review

57 Scopus citations


In this paper, we present a four-step technique for simultaneously estimating a human's anthropometric measurements (up to a scale parameter) and pose from a single image. The user initially selects a set of image points that constitute the projection of selected landmarks. Using this information, along with a priori statistical information about the human body, a set of plausible segment length estimates are generated. The third step produces a set of plausible poses based on joint limit constraints using a geometric method. In the fourth step, pose and anthropometric measurements are obtained by minimizing an appropriate cost function subject to the associated constraints. The novelty of our approach is the use of anthropometric statistics to constrain the estimation process that allows the simultaneous estimation of both anthropometry and pose. We demonstrate the accuracy, advantages and limitations of our method for various classes of both synthetic and real input data.

Original languageEnglish (US)
Pages (from-to)669-676
Number of pages8
JournalProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
StatePublished - 2000
EventIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000 - Hilton Head Island, SC, USA
Duration: Jun 13 2000Jun 15 2000

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition


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