In this talk and a sequel given by Amarjit Budhiraja we will discuss how variational representations can be used to develop an efficient methodology for large deviations analysis, especially in the infinite dimensional setting. This talk will start by reviewing the use of representations in a simple setting. We then discuss the proof of representations for infinite dimensional Brownian motion, and an application to an estimation problem in image matching. If time permits we will discuss some of the new features present when there is Poisson noise, a topic that will be completed in the sequel.