deletions | additions       diff --git a/Methodology Video Data.tex b/Methodology Video Data.tex  index ec70a1e..5973d9e 100644  --- a/Methodology Video Data.tex  +++ b/Methodology Video Data.tex 
...
\subsection{Video Data}  Road user trajectories are extracted from video data using computer vision.For more information on computer vision, see section \ref{software}.  \subsubsection{Trajectories: Positions in Space and Time (x,y,t)} 
...
Depending on the steps taken to minimise tracking areas, video-based feature tracking functions best over study areas of 50-100m in length with high-to-medium speed, low-to-medium density flows.  A sample of road user trajectories is presented in Figure~\ref{fig:conflict-video}. For more information on computer vision, see section \ref{software}.  \subsubsection{Derived Data: Velocity & Acceleration}  Velocity and acceleration measures are derived through differentiation from position and velocity over time respectively. These are 2-dimensional vectors with a magnitude (speed and acceleration) and a heading. The heading of the velocity vector is typically used to determine the orientation of the vehicle.