7.3

Application in MRF Object Recognition

The theory is applied to the parameter estimation for MRF object recognition where the form of the energy is derived based on MRFs. MRF modeling provides one approach to optimization-based object recognition [Modestino and Zhang 1989 ,Cooper 1990 ,Baddeley and van Lieshout 1992 ,Kim and Yang 1992 ,Li 1994a]. The MAP solution is usually sought. The posterior distribution of configurations f is of Gibbs

where Z is a normalizing constant called the partition function and is the posterior energy function measuring the global of f. In the following, is defined and converted to the linear form .

• 7.3.1 Posterior Energy
• 7.3.2 Energy in Linear Form
• 7.3.3 How Minimal Configuration Changes
• 7.3.4 Parametric Estimation under Gaussian Noise