deletions | additions       diff --git a/section_Trajectories_analysis_for_soccer__.tex b/section_Trajectories_analysis_for_soccer__.tex  index 9a37cf8..83671ec 100644  --- a/section_Trajectories_analysis_for_soccer__.tex  +++ b/section_Trajectories_analysis_for_soccer__.tex 
...
\subsection{Trajectories}  The current works on soccer match analysis managed to give semantic data and most of the time they used extra data bring brought  in several match matches  or championship. In this project we managed to find patterns in the paths of the players clustering players trajectories given only the video of a match filmed with a multi-camera system. The problem of players with multiple camera even if their paths may intersect over long period of time have been achieved in \cite{Ben_Shitrit_2011}. Our contribution is to provided an well fitted similarity measure between trajectories which allows the clustering of the players' trajectories according to the interdependency of their path using clustering via Linear  Yet only discrete trajectories are available in the form of array which can be of different sizes with different time discretization or with different speed.