Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/911A839B-70B5-4FB1-BB75-9C1597154D63 | - |
| Αναγνωριστικό | https://link.springer.com/article/10.1007%2Fs11042-015-2513-9 | - |
| Αναγνωριστικό | https://doi.org/10.1007/s11042-015-2513-9 | - |
| Γλώσσα | en | - |
| Μέγεθος | 33 pages | en |
| Τίτλος | 3D measures exploitation for a monocular semi-supervised fall detection system | en |
| Δημιουργός | Makantasis Konstantinos | en |
| Δημιουργός | Μακαντασης Κωνσταντινος | el |
| Δημιουργός | Protopapadakis Eftychios | en |
| Δημιουργός | Πρωτοπαπαδακης Ευτυχιος | el |
| Δημιουργός | Doulamis Anastasios | en |
| Δημιουργός | Δουλαμης Αναστασιος | el |
| Δημιουργός | Doulamis Nikolaos D. | en |
| Δημιουργός | Matsatsinis Nikolaos | en |
| Δημιουργός | Ματσατσινης Νικολαος | el |
| Εκδότης | Springer Verlag | en |
| Περίληψη | Falls 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 |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2018-06-28 | - |
| Ημερομηνία Δημοσίευσης | 2016 | - |
| Θεματική Κατηγορία | Camera self calibration | en |
| Θεματική Κατηγορία | Fall detection | en |
| Θεματική Κατηγορία | Image motion analysis | en |
| Θεματική Κατηγορία | Semi-supervised learning | en |
| Βιβλιογραφική Αναφορά | K. 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/s11042-015-2513-9 | en |
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