1. Centre for Research and Prevention of Injuries-CEREPRI, Fact Sheet: Prevention of Falls among Elderly, European Network for Safety among Elderly (2007), http://www.injuryobservatory.net/wp-content/uploads/2012/08/Older-Guide-Prevention-of-Falls.pdf
2. J. LiuJ. Yang, “Action recognition using spatiotemporal features and hybrid generative/discriminative models,” J. Electron. Imaging21(2), 023010 (2012).JEIME51017-9909 http://dx.doi.org/10.1117/1.JEI.21.2.023010
3. H. Jainet al., “Recognizing human gestures using a novel SVM tree,” Proc. SPIE8300, 83000M (2012). http://dx.doi.org/10.1117/12.908087
4. Y. WangG. Mori, “Hidden part models for human action recognition: probabilistic vs. max-margin,” IEEE Trans. Pattern Anal. Mach. Intell.33(7), 1310–1323 (2011).ITPIDJ0162-8828 http://dx.doi.org/10.1109/TPAMI.2010.214
5. N. Nouryet al., “Fall detection—principles and methods,” in Proc. 29th Annual Int. Conf. IEEE Engineering in Medicine and Biology Society (EMBS 2007), Antalya, Turkey, pp. 1663–1666 (2007)
6. A. LeoneG. DiracoP. Siciliano, “Detecting falls with 3D range camera in ambient assisted living applications: a preliminary study,” Med. Eng. Phys.33(6), 770–781 (2011).MEPHEO1350-4533 http://dx.doi.org/10.1016/j.medengphy.2011.02.001
7. C. KawatsuJ. LiC. Chung, “Development of a fall detection system with Microsoft Kinect,” in Robot Intelligence Technology and Applications 2012, J.-H. KimE. T. MatsonH. MyungP. Xu, Eds., Advances in Intelligent Systems and Computing, Vol. 208, pp. 623–630, Springer, Berlin (2013)
8. B. ToreyinY. DedeogluA. Cetin, “HMM based falling person detection using both audio and video,” in 2006 IEEE 14th Signal Processing and Communications Applications, pp. 1–4 (2006)
9. D. Andersonet al., “Recognizing falls from silhouettes,” in 28th Annual Int. Conf. IEEE Engineering in Medicine and Biology Society (EMBS ’06), pp. 6388–6391 (2006)
10. V. VishwakarmaC. MandalS. Sural, “Automatic detection of human fall in video,” in Proc. 2nd Int. Conf. Pattern Recognition and Machine Intelligence (PReMI’07), pp. 616–623, Springer-Verlag, Berlin (2007)
11. J. Willemset al., “A video-based algorithm for elderly fall detection,” in World Congress on Medical Physics and Biomedical Engineering, Munich, Germany, Vol. 25/5, pp. 312–315 (2009)
12. M. KhanH. Habib, “Video analytic for fall detection from shape features and motion gradients,” Lect. Notes Eng. Comput. Sci.2179(2), 1311–1316 (2009)
13. “YOLO: Real-Time Object Detection”, https://pjreddie.com/darknet/yolo/