Wayfinding Behavior Detection by Smartphone
Wayfinding Behavior Detection by Smartphone
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DOI：
10.1109/aina.2018.00078
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Ryosuke Narimoto;Shugo Kajita;Hirozumi Yamaguchi;T. Higashino
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文献类型：
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作者：
Ryosuke Narimoto;Shugo Kajita;Hirozumi Yamaguchi;T. Higashino
在前往目的地的过程中，我们通常依靠地图上的视听信息和我们的视觉构建的认知地图。然而，真实地图和我们认知地图之间的错误或差距往往会让我们感到困惑，从而导致“寻路”。在这种寻路状态下，我们倾向于采取漫游等行为来感知错误和收集周围环境的信息。如果这种行为可以被智能手机检测到，我们可以在智能手机上设计新的应用程序，例如，虚拟“礼宾”，当我们迷路时及时帮助我们。此外，在大型博物馆和主题公园中，抓住人们可能迷路的地方，安装或改进指示牌和指示，以支持游客，将是有用的。本文提出了一种利用智能手机传感器从行走特征中检测个体寻路行为的方法。在初步实验的基础上，我们提取了可以通过Android操作系统采集的传感器数据特征，且不存在隐私问题，并构建了用户状态“正常”和“寻路”的二元分类器。通过17名和104名受试者的两次现场实验，我们确认我们的分类器分别达到了0.93和0.85的F-measure。
While heading to a destination, we usually rely on our cognitive map constructed by audiovisual information from maps and our sight. However, errors or gaps between the real and our cognitive map often confuse us and lead to "wayfinding". In such a wayfinding state, we tend to take actions like wandering for perceiving errors and gathering information about surrounding environment. If such behavior can be detected by smartphones, we may design new applications on the smartphones, for instance, virtual "concierge" that timely helps us when we lose our ways. Also grasping spots where people are likely to lose their ways in large museums and theme parks would be useful to install or improve the signs and directions to support visitors. In this paper, we propose a method to detect individuals' wayfinding behavior from walking features by smartphone sensors. Based on the preliminary experiment, we extract sensor data features that can be collected through Android OS without privacy concerns, and build a binary classifier of user states, "normal" and "wayfinding". Through the two field experiments with 17 and 104 subjects, we have confirmed that our classifier achieved the F-measure of 0.93 and 0.85, respectively.