Sleep comfort analysis using a part-based mixture model with nighttime infrared video

This work investigated a new challenging problem: how to analyze human sleep comfort which is an urgent problem in intelligent home and medical supervision, especially in intelligent temperature control of air conditioners. To overcome this problem, a novel part-based mixture model is proposed to es...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2017-10, Vol.259, p.66-75
Main Authors: Su, Lumei, Xu, Min
Format: Article
Language:English
Subjects:
Human sleep comfort estimation
Part-based mixture model
Sleep posture feature extraction
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Summary:This work investigated a new challenging problem: how to analyze human sleep comfort which is an urgent problem in intelligent home and medical supervision, especially in intelligent temperature control of air conditioners. To overcome this problem, a novel part-based mixture model is proposed to estimate human sleep comfort. Unlike conventional human sleep comfort analysis using uncomfortable and expensive wearable-device, a remote infrared camera and a cheap temperature sensor are used to collect human sleep posture and real-time temperature information. Moreover, a robust sleep posture feature extraction method is firstly proposed to describe sleep comfort not matter human body is covered by a sheet or not. Experiments on a custom-made database demonstrated that the proposed method has promising performance for on-line human sleep comfort analysis.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2016.08.128