Shape, Depth, And Nonrigid Motion From Profiles

Demetri Terzopoulos; Andrew Witkin; Michael Kass

doi:10.1117/12.946981

29 March 1988 Shape, Depth, And Nonrigid Motion From Profiles

Demetri Terzopoulos, Andrew Witkin, Michael Kass

Proceedings Volume 0937, Applications of Artificial Intelligence VI; (1988) https://doi.org/10.1117/12.946981
Event: 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, 1988, Orlando, FL, United States

Abstract

Inferring the 3D structures of nonrigidly moving objects from natural images is a difficult yet basic problem in computational vision. Our approach makes use of dynamic, elastically deformable models. These physically-based 3D models offer the geometric flexibility to satisfy a diversity of visual constraints. Constraints are encoded as forces which act on the models to mold their shapes, place them in proper depth, and carry them through motions so as to best account for the available image data. We demonstrate the recovery of shape, depth, and nonrigid motion from object profiles (occluding contours) in natural images. This article reviews our approach; mathematical details are found in the primary sources.

Citation Download Citation

Demetri Terzopoulos, Andrew Witkin, and Michael Kass "Shape, Depth, And Nonrigid Motion From Profiles", Proc. SPIE 0937, Applications of Artificial Intelligence VI, (29 March 1988); https://doi.org/10.1117/12.946981

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