Contents:

1. Introduction ; 2. The Bayes paradigm, estimation and information measures ; 3. Probabilistic directed acyclic graphs and their entropies ; 4. Markov random fields on undirected graphs ; 5. Gaussian random fields on undirected graphs ; 6. The canonical representations of general pattern theory ; 7. Matrix group actions transforming patterns ; 8. Manifolds, active modes, and deformable templates ; 9. Second order and Gaussian fields ; 10. Metrics spaces for the matrix groups ; 11. Metrics spaces for the infinite dimensional diffeomorphisms ; 12. Metrics on photometric and geometric deformable templates ; 13. Estimation bounds for automated object recognition ; 14. Estimation on metric spaces with photometric variation ; 15. Information bounds for automated object recognition ; 16. Computational anatomy: shape, growth and atrophy comparison via diffeomorphisms ; 17. Computational anatomy: hypothesis testing on disease ; 18. Markov processes and random sampling ; 19. Jump diffusion inference in complex scenes