Video surveillance fall detection and alarm system in FPGA

被引:0
|
作者
Wang P. [1 ]
Wang H. [1 ]
Kong F.-N. [1 ]
Yao G. [1 ]
机构
[1] School of Electric and Electronics Engineering, Harbin University of Science and Technology, Harbin
关键词
Fall detection; Field programmable gate array; Frame subtraction method; General packet radio service; Video surveillance;
D O I
10.15938/j.emc.2019.08.015
中图分类号
学科分类号
摘要
As the injury caused by falling is usually serious for the elderly living alone, it is necessary for them to get timely assistance. This paper is to build a FPGA-based hardware implementation of fall detection and alarm system based on video surveillance. Firstly, the moving object contour was extracted through frame subtraction method. Secondly, the fall case can be judged from the aspect ratio and effective area ratio of bounding box. Finally, the result was modified based on the change of body centroid. Then the detection system made sound and light alarms and sent messages to the elder's family or the community via general packet radio service (GPRS). The experimental results demonstrate the frame processing speed is 24.86 fps and the average response time for alarming is 0.51 s. Besides, the accuracy of this fall detection system is up to 96%. This system satisfices the requirement of real-time and the error alarm rate is low. © 2019, Harbin University of Science and Technology Publication. All right reserved.
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页码:122 / 128
页数:6
相关论文
共 21 条
  • [11] Geng W., Sun Z., Guo J., A novel methed forming SPWM wave based on series hybrid algorithms, Electric Machines and Control, 20, 10, (2016)
  • [12] Zhang Q., Xie Z., Liu H., Et al., Design of modular joint controller based on FPGA witn software/hardware co-design methods, Electric Machines and Control, 17, 8, (2013)
  • [13] Ong P.S., Ooi C.P., Chang Y.C., Et al., A FPGA-based hardware implementation of visual based fall detection, IEEE Region 10 Symposium, pp. 397-402, (2014)
  • [14] Li B., Guan T., Modeling and sliding mode control of electric vehicle charger control system, Electric Machines and Control, 22, 2, (2018)
  • [15] Lin C., Wang K., Xia Y., Et al., Detection method of moving object with small displacement, Journal of Optoelectronics.Laser, 22, 3, (2011)
  • [16] Jia P., Xu N., Zhang Y., Automatic target recognition based on local feature extraction, Optics and Precision Engineering, 21, 7, (2013)
  • [17] Lu D., Liu C., Yan J., Et al., Total least square input estimation in tracking maneuver target, Electric Machines and Control, 3, (2006)
  • [18] Abdelhedi S., Bourguiba R., Mouine J., Et al., Development of a two-threshold-based fall detection algorithm for elderly health monitoring, IEEE Tenth International Conference on Research Challenges in Information Science, pp. 1-5, (2016)
  • [19] Chen X., Liao J., Li B., Et al., Foreground detection based on modified ViBe in dynamic background, Optics and Precision Engineering, 22, 9, (2014)
  • [20] Zhang G., Xie M., Design of visual based-FPGA Ping-Pang game with multi-models, IEEE Circuits, Communications and System, pp. 31-34, (2010)