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3D measures exploitation for a monocular semi-supervised fall detection system

Makantasis Konstantinos, Protopapadakis Eftychios, Doulamis Anastasios, Doulamis Nikolaos D., Matsatsinis Nikolaos

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URIhttp://purl.tuc.gr/dl/dias/911A839B-70B5-4FB1-BB75-9C1597154D63-
Identifierhttps://link.springer.com/article/10.1007%2Fs11042-015-2513-9-
Identifierhttps://doi.org/10.1007/s11042-015-2513-9-
Languageen-
Extent33 pagesen
Title3D measures exploitation for a monocular semi-supervised fall detection systemen
CreatorMakantasis Konstantinosen
CreatorΜακαντασης Κωνσταντινοςel
CreatorProtopapadakis Eftychiosen
CreatorΠρωτοπαπαδακης Ευτυχιοςel
CreatorDoulamis Anastasiosen
CreatorΔουλαμης Αναστασιοςel
CreatorDoulamis Nikolaos D.en
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
PublisherSpringer Verlagen
Content SummaryFalls have been reported as the leading cause of injury-related visits to emergency departments and the primary etiology of accidental deaths in elderly. Thus, the development of robust home surveillance systems is of great importance. In this article, such a system is presented, which tries to address the fall detection problem through visual cues. The proposed methodology utilizes a fast, real-time background subtraction algorithm, based on motion information in the scene and pixels intensity, capable to operate properly in dynamically changing visual conditions, in order to detect the foreground object. At the same time, it exploits 3D space’s measures, through automatic camera calibration, to increase the robustness of fall detection algorithm which is based on semi-supervised learning approach. The above system uses a single monocular camera and is characterized by minimal computational cost and memory requirements that make it suitable for real-time large scale implementations.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-06-28-
Date of Publication2016-
SubjectCamera self calibrationen
SubjectFall detectionen
SubjectImage motion analysisen
SubjectSemi-supervised learningen
Bibliographic CitationK. Makantasis, E. Protopapadakis, A. Doulamis, N. Doulamis and N. Matsatsinis, "3D measures exploitation for a monocular semi-supervised fall detection system," Multimed. Tools Appl., vol. 75, no. 22, pp. 15017-15049, Nov. 2016. doi: 10.1007/s11042-015-2513-9en

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