(Non-)rigid motion interpretation : a regularized approach
- 22 March 1988
- journal article
- research article
- Published by The Royal Society in Proceedings of the Royal Society of London. B. Biological Sciences
- Vol. 233 (1271) , 217-234
- https://doi.org/10.1098/rspb.1988.0020
Abstract
Determining 3D motion from a time-varying 2D image is an ill-posed problem; unless we impose additional constraints, an infinite number of solution is possible. The usual constraint is rigidity, but many naturally occurring motions are not rigid and not even piecewise rigid. A more general assumption is that the parameters (or some of the parameters) characterizing the motion are approximately (but not exactly) constant in any sufficiently small region of the image. If we know the shape of a surface we can uniquely recover the smoothest motion consistent with image data and the known structure of the object, through regularization. This paper develops a general paradigm for the analysis of non-rigid motion. The variational condition we obtain includes many previously studied constraints as ''special cases''. Among them are isometry, rigidity and planarity. If the variational condition is applied at multiple scales of resolution, it can be applied to turbulent motion. Finally, it is worth noting that our theory does not require the computation of corresponding (optic flow or discrete displacements), and it is effective in the presence of motion discontinuities.Keywords
This publication has 13 references indexed in Scilit:
- Shape and motion of nonrigid bodiesComputer Vision, Graphics, and Image Processing, 1986
- The computation of structure from fixed-axis motion: Nonrigid structuresBiological Cybernetics, 1985
- Maximizing Rigidity: The Incremental Recovery of 3-D Structure from Rigid and Nonrigid MotionPerception, 1984
- Monocular depth perception from optical flow by space time signal processingProceedings of the Royal Society of London. B. Biological Sciences, 1983
- Displacement vectors derived from second-order intensity variations in image sequencesComputer Vision, Graphics, and Image Processing, 1983
- Matching Coding to Scenes to Enhance EfficiencyPublished by Springer Nature ,1983
- The interpretation of biological motionBiological Cybernetics, 1982
- A computer algorithm for reconstructing a scene from two projectionsNature, 1981
- Determining optical flowArtificial Intelligence, 1981
- The interpretation of a moving retinal imageProceedings of the Royal Society of London. B. Biological Sciences, 1980