Abnormal Event Detection using Microsoft Kinect in a Smart Home

被引：0

作者：

Lin, Hsiu-Yu ^{[1
]}

Hsueh, Yu-Ling ^{[1
]}

Lie, Wen-Nung ^{[2
]}

机构：

[1] Natl Chung Cheng Univ, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[2] Natl Chung Cheng Univ, Dept Elect Engn, Taipei, Taiwan

来源：

2016 INTERNATIONAL COMPUTER SYMPOSIUM (ICS) | 2016年

关键词：

Fall detection; Deep learning; Data mining; Convolutional neural network; Long short-term memory network;

D O I：

10.1109/ICS.2016.63

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：285 / 289

页数：5

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