Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/911A839B-70B5-4FB1-BB75-9C1597154D63 | - |
| Identifier | https://link.springer.com/article/10.1007%2Fs11042-015-2513-9 | - |
| Identifier | https://doi.org/10.1007/s11042-015-2513-9 | - |
| Language | en | - |
| Extent | 33 pages | en |
| Title | 3D measures exploitation for a monocular semi-supervised fall detection system | en |
| Creator | Makantasis Konstantinos | en |
| Creator | Μακαντασης Κωνσταντινος | el |
| Creator | Protopapadakis Eftychios | en |
| Creator | Πρωτοπαπαδακης Ευτυχιος | el |
| Creator | Doulamis Anastasios | en |
| Creator | Δουλαμης Αναστασιος | el |
| Creator | Doulamis Nikolaos D. | en |
| Creator | Matsatsinis Nikolaos | en |
| Creator | Ματσατσινης Νικολαος | el |
| Publisher | Springer Verlag | en |
| Content Summary | 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 |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2018-06-28 | - |
| Date of Publication | 2016 | - |
| Subject | Camera self calibration | en |
| Subject | Fall detection | en |
| Subject | Image motion analysis | en |
| Subject | Semi-supervised learning | en |
| Bibliographic Citation | 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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