Fall Detection System Based on Mobile Robot

This paper proposed an accurate fall detection algorithm based on the feature of whole human body. The feature is extracted from convolutional neural network. The implementation of algorithm is integrated into a hardware system based on a visual mobile robot platform. To ensure the robustness and flexibility of algorithm in actual situation, a set of systemic strategies was applied on mobile robot. Finally, sufficient experiments on public dataset were conduct on our algorithm. Moreover, in a real indoor scene, experiment results proved the efficiency and precision of the designed fall detection system.

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