deletions | additions       diff --git a/section_Methodology_The_approach_proposed__.tex b/section_Methodology_The_approach_proposed__.tex  index c59a9f5..2be5b50 100644  --- a/section_Methodology_The_approach_proposed__.tex  +++ b/section_Methodology_The_approach_proposed__.tex 
...
\item \textbf{Object integrity verification}: verify any corruption in the data structure.  \item \textbf{Warm-up errors at scene edges}: vehicles entering image space are only partially tracked until they come within full view, and therefore are lacking in number of tracked features which causes issues with feature grouping.  \item \textbf{Duplicate detection removal}: based on proximity and trajectory similarity.  \item \textbf{Outlier point split}: when two distinct objects within the scene are grouped together creating a single object which seems to teleport instantly accross the scene. These are split at the time of teleportation  \item \textbf{Stub removal}: minimum trajectory dwell time of 0.66~s.  \item \textbf{Alignment filtering}: if alignment metadata (lane and sidewalk centerlines) exists, objects which deviate significantly from any typical movements can be flagged for manual review as either a severe traffic infraction or a tracking error.  \end{itemize} 
...
Transferability is thus verified by applying each set of optimized tracking parameters to each of the other annotated sequences. The full ten minute annotated videos are used to calculate the MOTA, which are then compared to the optimized tracking performance and reported also as a percentage of the maximum MOTA. This is done to avoid potential bias from the site selection and vehicle composition, which may lower the MOTA result compared to other cameras, despite having similar relative tracking performance results.