\documentclass[a4paper,12pt,pdftex]{exam}

\newcommand{\ptitle}{Eye tracker}
\input{../header.tex}
\firstpagefooter{Supervisor: Jan Grewe}{phone: 29 74588}%
{email: jan.grewe@uni-tuebingen.de}

\begin{document}

\input{../instructions.tex}


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\section*{Analysis of eye trajectories.}
In this project you will analyse eye-tracking data (courtesy of the
Mallot department). In this task the subject had to memorize the
positions of targets that can be only learned with active gaze
shifts. The eye movements during training and test are recorded.

\begin{questions}
  \question In the accompanying dataset you find six variables. (i)
  \textit{eye\_found} a logical array indicating whether the eye was
  found by the tracker. (ii, iii) \textit{gaze\_x} and
  \textit{gaze\_y} containing the x- and y-position of the gaze. They
  relate to a screen with 1280x1024 pixel resolution. (iv)
  \textit{frame\_time} containing time stamps for each frame. (v)
  \textit{marker\_time} containing the time of the last marker. (vi)
  \textit{marker\_count} the count of the markers. All entries with
  the same marker belong to the same trial.
  \begin{parts}
    \part Cut the data in chunks belonging to the same trial.
    \part Characterize the eye movements statistically, e.g. with eye
    speed and/or accelerations.
    \part Detect and correct the eye traces for instances in which the 
    eye was not correctly detected. Interpolate linearily in these sections. 
    \part Create a 'heatmap' plot that shows the eye trajectories 
    for one or two (nice) trials.
    \part Use the \verb+kmeans+ clustering function to 
    identify fixation points. Manually select a good number of cluster
    centroids. 
  \end{parts}
\end{questions}

\end{document}