deletions | additions       diff --git a/Methodology Complementary Data.tex b/Methodology Complementary Data.tex  index a4d2505..967b158 100644  --- a/Methodology Complementary Data.tex  +++ b/Methodology Complementary Data.tex 
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With the exception of speed and vehicle counts, vehicle trajectories offer little insight without context. Complementary data about the scene is collected in order to perform traffic studies and for higher-level interpretation. This data includes a wide variety of scene descriptors and design geometry attributes characterizing the factors under study.  \subsubsection{Analysis Area}  The analysis area is a bounding box which confines analysis to a particular region of the scene. This serves to i) reject areas of the image with unsatisfactory feature tracking (particularly at the edges of the video), and ii) confine analysis to a particular region. For a cross-sectional or before-after study, analysis areas should to the same region of the roadway as much as possible.  The analysis area differs from a mask used during feature tracking which instructs the computer vision to ignore certain portions of the image. Feature tracking which uses a mask is still prone to "warm-up" tracking errors at the edge of the mask.  \subsubsection{Alignments}  Trajectory clustering is the first step in scene interpretation. Trajectory clustering is an abstract representation of movements along prototypical paths through a scene, called alignments. This is the foundation for relating spatial position with road geometry and, in particular, position of moving objects in relation to lanes and sidewalks. The alignment is represented as a simple series of points with a begining and end, typically in the same direction is the majority of flows along this path. This process introduces a new coordinate system which maps a position of a moving object in cartesian space to a position in curvilinear space