- \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. 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.
-
-
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