\section{Introduction}
\label{sec:introduction}

The turning 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 information, but not reveal too much privacy
like the RGB camera.

{\bf Contribution}

In this work, we deployed multiple low resolution thermal cameras to monitor the
turning over frequency while sleeping. We propose a data fusing and enhancement method
to fuse multiple Grideye
thermal sensors into a low-resolution thermal image, and use Super-resolution techniques
to enhance the resolution. With our pose detection method, we have 65\% accuracy of pose
detection, and 50\% recall rate and 83\% precision of turning over detection.


%The remaining of this paper is organized as follows. Section~\ref{sec:bk_related}
%presents background for developing the methods. Section~\ref{sec:design} presents
%the system architecture, and the developed mechanisms.  Section~\ref{sec:eval}
%presents the evaluation results of proposed mechanism and Section~\ref{sec:conclusion} summaries our works.

 
