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Proceedings Paper

Shape representation and nonrigid motion tracking using deformable superquadrics
Author(s): Dimitri N. Metaxas; Demetri Terzopoulos
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Paper Abstract

This paper presents a physically-based approach to the recovery of shape and nonrigid 3-D motion and the tracking of nonrigid objects. The approach makes use of deformable superquadrics (with additional parameterized tapering and bending deformations), dynamic models that offer global deformation parameters which capture large scale features and local deformation parameters that capture the details of complex shapes. We further present a generalization of the formulation to handle physically-based point-to-point constraints between models and to formally account for noise in the data using a recursive estimation technique based on Kalman filtering. such constraints enable us to automatically assemble object models from interconnected deformable superquadric parts. The equations of motion governing the behavior of the models make them responsive to externally applied forces. These composite models can be used to track the motions of articulated, flexible objects. Models are fitted to visual data by transforming the data into forces and simulating the equations of motion through time to adjust the translational, rotational, global, and local deformational degrees of freedom of the models. We present model fitting and motion tracking experiments involving 2-D and 3- D data.

Paper Details

Date Published: 1 September 1991
PDF: 9 pages
Proc. SPIE 1570, Geometric Methods in Computer Vision, (1 September 1991); doi: 10.1117/12.49982
Show Author Affiliations
Dimitri N. Metaxas, Univ. of Toronto (United States)
Demetri Terzopoulos, Univ. of Toronto (Canada) and Schlumberger Lab. for Computer Science (Canada)

Published in SPIE Proceedings Vol. 1570:
Geometric Methods in Computer Vision
Baba C. Vemuri, Editor(s)

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