Neural network based event estimation on lifelog from various sensors

Masayuki Ono, Kunihiro Nishimura, T. Tanikawa, M. Hirose
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引用次数: 3

Abstract

The data related to our life experiences is called lifelog, which can easily be collected with mobile electronic devices in recent years. Although lifelog research has been conducted for a long time, practical applications such as a memory assistant system have not been fully developed yet. This is mainly due to the lack of methods to structurize the lifelog data efficiently. In our research, we developed a method for structuring a lifelog consisting of data from various sensors, focusing on event estimation with neural network. In an evaluation experiment, we captured lifelog data with a device that has various sensors, and then we estimated the events, i.e., the participantsf activities. As a result, the system correctly estimated events 70.4% of the time. We also created a lifelog viewer to visualized the data based on the result of event estimation.
基于神经网络的各种传感器生命日志事件估计
与我们的生活经历相关的数据被称为生活日志,近年来可以很容易地用移动电子设备收集。虽然对生活日志的研究已经进行了很长时间,但记忆辅助系统等实际应用还没有完全开发出来。这主要是由于缺乏有效地结构化生命日志数据的方法。在我们的研究中,我们开发了一种构建由各种传感器数据组成的生命日志的方法,重点是用神经网络进行事件估计。在一个评估实验中,我们用一个带有各种传感器的设备捕获了生活日志数据,然后我们估计了事件,即参与者的活动。因此,系统正确估计事件的概率为70.4%。我们还创建了一个生活日志查看器,以便根据事件估计的结果将数据可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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