Classification of Indoor Actions through Deep Neural Networks

Filippo Vella, A. Augello, U. Maniscalco, Vincenzo Bentivenga, S. Gaglio
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引用次数: 3

Abstract

The raising number of elderly people urges the research of systems able to monitor and support people inside their domestic environment. An automatic system capturing data about the position of a person in the house, through accelerometers and RGBd cameras can monitor the person activities and produce outputs associating the movements to a given tasks or predicting the set of activities that will be executes. We considered, for the task the classification of the activities a Deep Convolutional Neural Network. We compared two different deep network and analyzed their outputs.
基于深度神经网络的室内动作分类
老年人数量的增加促使研究能够在家庭环境中监测和支持老年人的系统。通过加速计和RGBd摄像头,自动系统捕获有关人在房屋中的位置的数据,可以监控人的活动,并产生将运动与给定任务相关联的输出,或预测将执行的一系列活动。我们考虑使用深度卷积神经网络对活动进行分类。我们比较了两种不同的深度网络,并分析了它们的输出。
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