Allan, For time-series, the path map gives the MAP estimate of a hidden continuous-valued series variable X given some sequence of observations Y. X can evolve nonlinearly and Y can be a nonlinear function of X. It's fully learnable. Examples in "Voice Puppetry" Proc SIGGRAPH99 (X=3D facial motion; Y=voice) "Shadow Puppetry" Proc ICCV99 (X=3D body motion; Y=shadows) There's a web-available summary at http://www.cis.ohio-state.edu/~szhu/workshop/Brand.html cheer, Matt Brand
- Continuous Bayesian Nets Allan Tucker
- Matthew Brand
