In this talk, I will discuss a system to determine ground-plane parameters in densely 
crowded scenes where use of geometric features such as parallel lines, or reliable 
estimates of agent dimensions, is often not possible. Using feature points tracked 
over short intervals, together with some plausible scene assumptions, we can estimate 
the parameters of the ground-plane to a sufficient degree of accuracy to correct 
usefully for perspective distortion. This paper describes feasibility studies 
conducted on controlled, simulated data to establish how different levels and 
types of noise affect the accuracy of the estimation, and a verification of 
the approach on live data, showing that the method is able to estimate ground-plane 
parameters to a sufficient level of detail to enhance the accuracy of trajectory 
analysis. I will then discuss an on-going extension to this work to estimate multiple 
planes within more complex scenes.