\title{Related Works}
\author{Jason Banich}
\date{\today}

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\maketitle


\paragraph{}
As cell phones get more powerful, they become usable for more and more
applications. Cell phones these days have many different sensors and components
built in, such as GPS, accelerometer, camera, internet, etc. Cell phones can be
used for almost everything these days, and are starting to become recognized as
tools for aiding people who are disabled.

\section{Zebra Crosswalk Detection}

\begin{figure}[htp]
  \centering
  \begin{center}
    \includegraphics[width=0.45\textwidth]{Zebra.jpg}
    \caption{Zebra Crosswalk}
    \label{fig:Zebra}
  \end{center}
\end{figure}

\paragraph{}
Zebra crosswalks are very common these days, and as such any crosswalk detection
program should be able to detect and handle them. These crosswalks are
identified by the zebra-like pattern seen in Figure \ref{fig:Zebra}. In order
to navigate these crosswalks, the pedestrian must remain within the lines at
all times.  A method for detecting these crosswalks was tested in ``Detecting
and locating crosswalks using a camera phone\cite{ZebraPhone}.'' The authors
proposed a method based on four steps:
\begin{enumerate}
  \item Extract straight line segments from the image
  \item Apply segmentation algorithm to group the detected segments
  \item Score the detected segments
  \item Use a pre-determined threshold to determine if enough horizontal line
  segments were in the image
\end{enumerate}

\paragraph{}
By doing so, they were able to achieve a high percentage accuracy on the
recognition of zebra crosswalks with blind users operating the cell phone.

\section{Two Stripe Crosswalk Detection}

\begin{figure}[htp]
  \centering
  \begin{center}
    \includegraphics[width=0.45\textwidth]{2Stripe.jpg}
    \caption{Two Stripe Crosswalk}
    \label{fig:Stripe}
  \end{center}
\end{figure}

\paragraph{}
The most common type of crosswalk is the ``two stripe crosswalk.'' These are
denoted by two parallel lines marking the boundaries of the crosswalk, as seen
in Figure \ref{fig:Stripe}. In order to navigate this crosswalk, the pedestrian
must stay within the two white lines as they make their way across the street. A
method for detecting these is as follows:
\begin{enumerate}
  \item Read accelerometer in phone to determine orientation of the phone in
  relation to gravity 
  \item Determine horizon line
  \item Discard data above the horizon line
  \item Use brightness of points to estimate if they are in the crosswalk
  stripes
  \item Draw the crosswalk lines on the image
\end{enumerate}

\paragraph{}
As with their Zebra results, they were able to obtain steady and consistent
and correct predictions through their work\cite{Crosswatch2Lane}.


\section{Walk Light Detection}

\begin{figure}[htp]
  \centering
  \begin{center}
    \includegraphics[width=0.45\textwidth]{walk.png}
    \caption{Walk Symbol}
    \label{fig:walk}
  \end{center}
\end{figure}

\paragraph{}
Detecting the ``Walk'' light is another feature that would be helpful for the
visually impaired pedestrian. If they are unable to see the walk symbol (as
seen in Figure \ref{fig:walk}, there is not an efficient way to know when its
safe to walk across the street other than listening to traffic. One such method involves using the phone's
accelerometer to find the horizon line, and discardinmg data below that line.
They also use other factors to narrow down the search, such as looking for a
green traffic light, and looking right below it for the walk
light\cite{WalkLightDetection}.

\section{Simple Lane Following Algorithm}
\paragraph{}
As autonomous cars start to become a reality, there are needs for algorithms
that can assist them in navigating and staying inside the lines. These
algorithms work by detecting the lines that are drawn on the pavement, and
instructing the car to stay in the center of these two lines. This is similar to
the crosswalk problem, in that you want the user to stay in between the two
lines, but different because you don't necessarily want the user to stay in the
precise center at all times, the main goal is to keep them inside the crosswalk.
One algorithm for lane following is as follows:
\begin{enumerate}
  \item Convert the image to grayscale
  \item Crop to the center portion of the image
  \item Identify the edges using an edge detection algorithm, and then draw the
  edges onto a new image
  \item Apply Hough line detection to find shapes in the edges
  \item Delete extraneous lines that were detected
  \item Reapply the lines that have been found to the main image and draw them
  on
\end{enumerate}
\paragraph{}
By following these steps, the image is processed and the lanes are returned,
which can then be used to direct the car. We should be able to adapt this
successfully to the two stripe crosswalks, and this should assist us in guiding
the user through the street\cite{SingleLane1}.


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