Diffusion processes which are widely used in low level vision are presented as a result of an underlying stochastic process. The short-time non-linear diffusion is interpreted as a Fokker-Planck equation which governs the evolution in time of a probability distribution for a Brownian motion on a Riemannian surface. The non linearity of the diffusion has a direct relation to the geometry of the surface. A short time kernel to the diffusion as well as generalizations are found.
|Number of pages||6|
|State||Published - 2001|
|Event||8th International Conference on Computer Vision - Vancouver, BC, United States|
Duration: 9 Jul 2001 → 12 Jul 2001
|Conference||8th International Conference on Computer Vision|
|Period||9/07/01 → 12/07/01|