Contour Inferences for Image Understanding
- 119 Downloads
We present a new approach to the algorithmic study of planar curves, with applications to estimations of contours in images. We construct spaces of curves satisfying constraints suited to specific problems, exploit their geometric structure to quantify properties of contours, and solve optimization and inference problems. Applications include new algorithms for computing planar elasticae, with enhanced performance and speed, and geometric algorithms for the estimation of contours of partially occluded objects in images.
Keywordscurve interpolation elastica partial occlusions shape completion
Unable to display preview. Download preview PDF.
- Do Carmo, M.P. 1976. Differential Geometry of Curves and Surfaces, Prentice Hall, Inc.Google Scholar
- Euler, L. 1744. Methodus Inveniendi Lineas Curvas Maximi Minimive Proprietate Gaudentes, Sive Solutio Problematis Isoperimetrici Lattisimo Sensu Accepti. Bousquet, Lausannae e Genevae, E65A. O. O. Ser. I, 24.Google Scholar
- Joshi, S., Srivastava, A., Mio, W., and Liu, X. 2004. Hierarchical Organization of Shapes for Efficient Retrieval. In Proc. ECCV 2004, LNCS, Prague, Czech Republic, pp. 570–581.Google Scholar
- Mio, W., Srivastava, A., and Liu, X. 2004b. Learning and Bayesian Shape Extraction for Object Recognition. In Proc. ECCV 2004, LNCS, Prague, Czech Republic, pp. 62–73.Google Scholar
- Mumford, D. 1994. Elastica and Computer Vision, Springer, New York. pp. 491–506.Google Scholar
- Royden, H. 1988. Real Analaysis, Prentice Hall.Google Scholar
- Sethian, J. 1996. Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision, and Material Science, Cambridge University Press.Google Scholar
- Weiss, I. 1988. 3D Shape Representation by Contours. Computer Vision, Graphics and Image Processing, 41:80–100.Google Scholar
- Williams, L. and Jacobs, D. 1997. Local Parallel Computation of Stochastic Completion Fields. Neural Computation, 9:837–858.Google Scholar