Abstract
Falling is one of the major risks for elderly people, kids and people with disabilities. The situation worsens when the victim suffers from serious injuries and is unable to get help on time. In this paper, we propose a method to detect a fall in real-time. The proposed detection method consists of three stages: Video analysis, Body Recognition and Trigger Alert. In this recognition system, human detection algorithms using OpenCV have been implemented. The application accuracy has been tested under different lighting settings and in different environment settings.
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CITATION STYLE
Mourey, J., Sehat Niaki, A., Kaplish, P., & Gupta, R. (2020). Human body fall recognition system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12015 LNCS, pp. 372–380). Springer. https://doi.org/10.1007/978-3-030-54407-2_31
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