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26 lines
1.2 KiB
26 lines
1.2 KiB
\section{Introduction}
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\label{sec:introduction}
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The turning over frequency while sleeping is an important index to quantify the
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health of elderly. Many wearable devices can also achieve the same purpose, but
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many study show that the elderly feel uncomfortable with wearing such devices
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all days. By the low resolution thermal camera, we
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can obtain the daily activities information, but not reveal too much privacy
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like the RGB camera.
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{\bf Contribution}
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In this work, we deployed multiple low resolution thermal cameras to monitor the
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turning over frequency while sleeping. We propose a data fusing and enhancement method
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to fuse multiple Grideye
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thermal sensors into a low-resolution thermal image, and use Super-resolution techniques
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to enhance the resolution. With our pose detection method, we have 65\% accuracy of pose
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detection, and 50\% recall rate and 83\% precision of turning over detection.
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%The remaining of this paper is organized as follows. Section~\ref{sec:bk_related}
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%presents background for developing the methods. Section~\ref{sec:design} presents
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%the system architecture, and the developed mechanisms. Section~\ref{sec:eval}
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%presents the evaluation results of proposed mechanism and Section~\ref{sec:conclusion} summaries our works.
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