Three-Dimensional Human Body Model Acquisition from Multiple Views View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1998-12

AUTHORS

Ioannis A. Kakadiaris, Dimitri Metaxas

ABSTRACT

We present a novel approach to the three-dimensional human body model acquisition from three mutually orthogonal views. Our technique is based on the spatiotemporal analysis of the deforming apparent contour of a human moving according to a protocol of movements. For generality and robustness our technique does not use a prior model of the human body and a prior body part segmentation is not assumed. Therefore, our technique applies to humans of any anthropometric dimension. To parameterize and segment over time a deforming apparent contour, we introduce a new shape representation technique based on primitive composition. The composed deformable model allows us to represent large local deformations and their evolution in a compact and intuitive way. In addition, this representation allows us to hypothesize an underlying part structure and test this hypothesis against the relative motion (due to forces exerted from the image data) of the defining primitives of the composed model. Furthermore, we develop a Human Body Part Decomposition Algorithm (HBPDA) that recovers all the body parts of a subject by monitoring the changes over time to the shape of the deforming silhouette. In addition, we modularize the process of simultaneous two-dimensional part determination and shape estimation by employing the Supervisory Control Theory of Discrete Event Systems. Finally, we present a novel algorithm which selectively integrates the (segmented by the HBPDA) apparent contours from three mutually orthogonal viewpoints to obtain a three-dimensional model of the subject's body parts. The effectiveness of the approach is demonstrated through a series of experiments where a subject performs a set of movements according to a protocol that reveals the structure of the human body. More... »

PAGES

191-218

References to SciGraph publications

  • 1996. Computational perception of scene dynamics in COMPUTER VISION — ECCV '96
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1023/a:1008071332753

    DOI

    http://dx.doi.org/10.1023/a:1008071332753

    DIMENSIONS

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