A Real-Time Fall Detection System for Maintenance Activities in Indoor Environments

Authors: D. Triantafyllou, S. Krinidis, D. Ioannidis, I. Metaxa, C. Ziazios and D. Tzovaras

Abstract

A real-time, multi-camera incident detection system for indoor environments is presented in this paper. The paper focuses on the detection of fall incidents while it highlights the leverage that such a system can provide to the human resources department of a shop-floor especially referring to the maintenance procedures. The proposed detection method extracts features that characterize a falling person’s trajectory, like vertical velocity and area variance, while the fall is described by Hidden Markov Models (HMM). The system utilizes only privacy preserving sensors. Experimental results illustrate its efficiency.

Citation

D. Triantafyllou, S. Krinidis, D. Ioannidis, I. Metaxa, C. Ziazios and D. Tzovaras, “A Real-Time Fall Detection System for Maintenance Activities in Indoor Environments”, 3rd IFAC AMEST Workshop, Biarritz, France, 19-21 October 2016

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