在智能家居中使用微软Kinect进行异常事件检测

Hsiu-Yu Lin, Yu-Ling Hsueh, W. Lie
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引用次数: 10

摘要

在本文中,我们提出了一个使用微软Kinect进行跌倒检测的连续深度学习模型。输入包括预处理的高分辨率RGB图像、Kinect采集的深度图像和光流图像。我们结合了卷积神经网络和长短期记忆网络等几种深度学习结构,用于连续的人体跌倒检测。最后,我们给出了实验结果来证明我们的方法的性能和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abnormal Event Detection Using Microsoft Kinect in a Smart Home
In this paper, we present a continuous deep learning model for fall detection using Microsoft Kinect. The input include pre-processed high-resolution RGB images, depth images collected by a Kinect and optical flow images. We combine several deep learning structures including convolutional neural networks and long short-term memory networks for continuous human fallen detection. Finally, we present experimental results to demonstrate the performance and utility of our approach.
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