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First draft of abstract and introduction

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\begin{abstract}
Abstract.
A low resolution infrared camera can use to collect the data of our daily
activity, and protect privacy. However, pose detection on an extremely low
resolution image will be a big challenge to deal with.
Many researches show that Super-resolution may improve the accuracy of
object detection on low resolution images.
%% long-term care?
In this work, we detect the turn over while sleeping.
To deal with low resolution image, we fuse the images from multiple infrared
cameras, and enhance the resolution by SRCNN. The noise not only from the sensor
itself but also the residual body temperature on bed after turn over.
\end{abstract}

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\section{Introduction}
\label{sec:introduction}
Introduction~\cite{Shih14a}
The turn over frequency while sleeping is an important index to quantify the
health of elderly. Many wearable devices can also achieve the same purpose, but
many study show that the elderly feel uncomfortable with wearing such devices
all days.\textcolor{red}{(source?)}. By the low resolution thermal camera, we
can obtain the daily activities informations, but not reveal too much privacy
like the RGB camera.
{\bf Contribution} Contribution
In this work, we deployed multiple low resolution thermal camera to monitor the
turn over frequency while sleeping. With multiple thermal camera and
Super-resolution techniques we can improve the accuracy of turn over detection
by XX\%.
The remaining of this paper is organized as follow. Section~\ref{sec:bk_related} presents related works and background for developing the methods. Section~\ref{sec:design} presents the system architecture, challenges, and the developed mechanisms. Section~\ref{sec:eval} presents the evaluation results of proposed mechanism and Section~\ref{sec:conclusion} summaries our works.

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