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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

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/911A839B-70B5-4FB1-BB75-9C1597154D63-
Αναγνωριστικόhttps://link.springer.com/article/10.1007%2Fs11042-015-2513-9-
Αναγνωριστικόhttps://doi.org/10.1007/s11042-015-2513-9-
Γλώσσαen-
Μέγεθος33 pagesen
Τίτλος3D measures exploitation for a monocular semi-supervised fall detection systemen
ΔημιουργόςMakantasis Konstantinosen
ΔημιουργόςΜακαντασης Κωνσταντινοςel
ΔημιουργόςProtopapadakis Eftychiosen
ΔημιουργόςΠρωτοπαπαδακης Ευτυχιοςel
ΔημιουργόςDoulamis Anastasiosen
ΔημιουργόςΔουλαμης Αναστασιοςel
ΔημιουργόςDoulamis Nikolaos D.en
ΔημιουργόςMatsatsinis Nikolaosen
ΔημιουργόςΜατσατσινης Νικολαοςel
ΕκδότηςSpringer Verlagen
ΠερίληψηFalls 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
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2018-06-28-
Ημερομηνία Δημοσίευσης2016-
Θεματική ΚατηγορίαCamera self calibrationen
Θεματική ΚατηγορίαFall detectionen
Θεματική ΚατηγορίαImage motion analysisen
Θεματική ΚατηγορίαSemi-supervised learningen
Βιβλιογραφική ΑναφοράK. 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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