The computer vision community is very familiar with Markov random field (MRF) modeling for numerous applications. In this talk, I will present an overview of the more general, but less popular, Markov point processes (MPP) and will highlight the connection between MRF and MPP and the advantages of MPP modeling for specific applications.  Recently,  several versions of MPP called ‘Marked’ point processes have been used in remote sensing/aerial imaging applications. I will discuss some of the applications and finally, present my recent work based on MPP.