On the improvement of anthropometry and pose estimation from a single uncalibrated image |
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Authors: | Email author" target="_blank">Carlos?BarrónEmail author Ioannis?A?Kakadiaris |
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Affiliation: | (1) Visual Computing Lab, Department of Computer Science, University of Houston, 4800 Calhoun, TX 77204-3010 Houston, USA |
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Abstract: | Recently, we developed a technique that allows semi-automatic 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. In this paper, 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 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 tenfold. We present our results over a variety of images to demonstrate the broad coverage of our algorithm.Published online: 1 September 2003 |
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Keywords: | Anthropometry Pose estimation Human motion estimation Tracking Articulated objects |
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