@inproceedings{Yun2013b,
abstract = {This paper presents a multi-camera motion capture system aiming to provide caregivers with timely access to the patient's health status through mobile communication devices. The major components include video capture, object detection, video coding and transmission, error concealment, and video analysis. Our contribution is twofold. First, several novel ideas are developed, including fast object detection, and content-aware and adaptive video coding and transmission. Second, all components are seamlessly integrated in a unified optimization framework dedicated for online data transmission. In the scenario, the subject walked on a treadmill with four tripod cameras capturing the video from different viewpoints. After video compression and transmission over a wireless sensor network, the remote receiver recovered the videos and performed multi-view motion capture for gait analysis. Experimental results show that the presented system design achieves better video quality than traditional video coding and transmission scheme, while the requirement for a low-cost, noninvasive and real-time healthcare monitoring system is accommodated. {\textcopyright} 2013 IEEE.},
author = {Ye, Yun and Ci, Song and Katsaggelos, Aggelos K. and Liu, Yanwei},
booktitle = {2013 IEEE International Conference on Multimedia and Expo (ICME)},
doi = {10.1109/ICME.2013.6607566},
isbn = {978-1-4799-0015-2},
issn = {19457871},
keywords = {Healthcare monitoring,multi-view motion capture,object detection,video coding and transmission,wireless communications},
month = {jul},
pages = {1--6},
publisher = {IEEE},
title = {{A multi-camera motion capture system for remote healthcare monitoring}},
url = {http://ieeexplore.ieee.org/document/6607566/},
year = {2013}
}

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After video compression and transmission over a wireless sensor network, the remote receiver recovered the videos and performed multi-view motion capture for gait analysis. Experimental results show that the presented system design achieves better video quality than traditional video coding and transmission scheme, while the requirement for a low-cost, noninvasive and real-time healthcare monitoring system is accommodated. © 2013 IEEE.","author":[{"propositions":[],"lastnames":["Ye"],"firstnames":["Yun"],"suffixes":[]},{"propositions":[],"lastnames":["Ci"],"firstnames":["Song"],"suffixes":[]},{"propositions":[],"lastnames":["Katsaggelos"],"firstnames":["Aggelos","K."],"suffixes":[]},{"propositions":[],"lastnames":["Liu"],"firstnames":["Yanwei"],"suffixes":[]}],"booktitle":"2013 IEEE International Conference on Multimedia and Expo (ICME)","doi":"10.1109/ICME.2013.6607566","isbn":"978-1-4799-0015-2","issn":"19457871","keywords":"Healthcare monitoring,multi-view motion capture,object detection,video coding and transmission,wireless communications","month":"jul","pages":"1–6","publisher":"IEEE","title":"A multi-camera motion capture system for remote healthcare monitoring","url":"http://ieeexplore.ieee.org/document/6607566/","year":"2013","bibtex":"@inproceedings{Yun2013b,\nabstract = {This paper presents a multi-camera motion capture system aiming to provide caregivers with timely access to the patient's health status through mobile communication devices. The major components include video capture, object detection, video coding and transmission, error concealment, and video analysis. Our contribution is twofold. First, several novel ideas are developed, including fast object detection, and content-aware and adaptive video coding and transmission. Second, all components are seamlessly integrated in a unified optimization framework dedicated for online data transmission. In the scenario, the subject walked on a treadmill with four tripod cameras capturing the video from different viewpoints. After video compression and transmission over a wireless sensor network, the remote receiver recovered the videos and performed multi-view motion capture for gait analysis. 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