Fall Detection with Kinect in Top View: Preliminary Features Analysis and Characterization
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-76111-4_16
Reference8 articles.
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2. Gasparrini, S., Cippitelli, E., Spinsante, S., Gambi, E.: A depth-based fall detection system using a kinect sensor. Sensors 14(2), 2756–2775 (2014). https://doi.org/10.3390/s140202756 . http://www.mdpi.com/1424-8220/14/2/2756
3. Han, J., Shao, L., Xu, D., Shotton, J.: Enhanced computer vision with microsoft kinect sensor: a review. IEEE Trans. Cybern. 43(5), 1318–1334 (2013). https://doi.org/10.1109/TCYB.2013.2265378
4. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;S Spinsante,2015
5. Spinsante, S., Gambi, E., De Santis, A., Montanini, L., Pelliccioni, G., Raffaeli, L., Rascioni, G.: Design and implementation of a smart home technological platform for the delivery of AAL services: from requirements to field experience, pp. 433–456. Healthcare Technologies. Institution of Engineering and Technology (2016). https://doi.org/10.1049/PBHE006E_ch21
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1. Fall Detection;Health Information Science;2022
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