On the improvement of anthropometry and pose estimation from a single uncalibrated image

C. Barron, I. A. Kakadiaris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


We developed a technique that allows semiautomatic estimation of anthropometry and pose from a single image. However, estimation was limited to a class of images for which an adequate number of human body segments were almost parallel to the image plane. We present a generalization of that estimation algorithm that exploits pairwise geometric relationships of body segments to allow estimation from a broader class of images. In addition, we refine our search space by constructing a fully populated discrete hyper-ellipsoid of stick human body models (SMs) in order to capture the variance of the statistical anthropometric information. As a result, a better initial estimate can be computed by our algorithm and thus the number of iterations needed during minimization are reduced by tenfold. We present our results over a variety of images to demonstrate the broad coverage of our algorithm.

Original languageEnglish (US)
Title of host publicationProceedings - Workshop on Human Motion, HUMO 2000
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)0769509398, 9780769509396
StatePublished - 2000
EventWorkshop on Human Motion, HUMO 2000 - Austin, United States
Duration: Dec 7 2000Dec 8 2000

Publication series

NameProceedings - Workshop on Human Motion, HUMO 2000


ConferenceWorkshop on Human Motion, HUMO 2000
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing


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