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https://www.um.edu.mt/library/oar/handle/123456789/124832
Title: | Student-t background modeling for persons' fall detection through visual cues |
Authors: | Makantasis, Konstantinos Doulamis, Anastasios Matsatsinis, Nikolaos F. |
Keywords: | Motion perception (Vision) Computer vision Falls (Accidents) -- Prevention Image analysis -- Mathematical models Electronic surveillance -- Technological innovations |
Issue Date: | 2012-05 |
Publisher: | Institute of Electrical and Electronics Engineers |
Citation: | Makantasis, K., Doulamis, A., & Matsatsinis, N. F. (2012, May). Student-t background modeling for persons' fall detection through visual cues. 13th International Workshop on Image Analysis for Multimedia Interactive Services, Dublin. 1-4. |
Abstract: | This article presents a robust, real-time background subtraction algorithm able to operate properly in complex dynamically changing visual conditions and indoor/outdoor environments, based on a single, cheap monocular camera, like a webcam. This algorithm uses an image grid and models each pixel of the grid as a mixture of adaptive Student-t distributions. This approach makes this algorithm robust and efficient, in terms of computational cost and memory requirements, and thus suitable for large scale implementations. The proposed algorithm is applied in the problem of humans’ fall detection that presents high complexity of visual content. Finally, the performances of this scheme and the scheme proposed in by the same authors, are compared. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/124832 |
Appears in Collections: | Scholarly Works - FacICTAI |
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Student t background modeling for persons fall detection through visual cues 2012.pdf Restricted Access | 344.18 kB | Adobe PDF | View/Open Request a copy |
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