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Paul St-Aubin added section_Literature_Review_subsection_Computer__.tex
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\section{Literature Review}
\subsection{Computer Vision in Traffic Applications}
Computer vision is used extensively in traffic applications as an instrument of data collection and monitoring. The two primary branches of computer vision in traffic applications include presence detection (sometimes referred to as virtual loops) and feature tracking. Presence detection has widespread commercial application due to its has a high degree of reliability; its primary application is in providing traffic counts, queue lengths, and basic presence detection. Feature tracking is a more complex application which tracks moving features within camera space continuously, providing accurate measures of position, velocity, and acceleration over time, but is generally less reliable than presence detection systems. The NGSIM project was one of the first large-scale video data collection projects making use of semi-automated vehicle tracking from freeway and urban arterials video data to obtain vehicle trajectories for traffic model calibrations \cite{Kim_2005}. Surrogate safety analysis also makes use of extensive trajectory data, for example with the early SAVEME project \cite{Ervin_2000, Gordon_2012}, and now more recently with extensive research projects such as Traffic-Intelligence \cite{saunier06feature-based, Jackson_2013}.
\subsection{Tracking Optimisation}
