Recognition of Group Mobility Level and Group Structure with Mobile Devices
Recognition of Group Mobility Level and Group Structure with Mobile Devices
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DOI：
10.1109/tmc.2017.2694839
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发表时间：
2018-04
影响因子：
7.9
通讯作者：
He Du;Zhiwen Yu;Fei Yi;Zhu Wang;Qi Han;Bin Guo
中科院分区：
文献类型：
--
作者：
He Du;Zhiwen Yu;Fei Yi;Zhu Wang;Qi Han;Bin Guo
监测群体的流动性和结构对于理解群体活动和社会关系至关重要。本文提出了利用移动设备对社会群体进行细粒度移动性分类和结构识别的算法。首先，我们提出了一种识别四个级别的群体移动性的方法，包括静止、漫步、行走和奔跑。其次，利用多种类型的移动传感器，提出了一种新的相对位置关系估计算法，以了解不同的运动群体结构。我们进行了现实生活中的实验，让12名志愿者以不同的小组在办公楼或购物中心以不同的速度和结构移动。实验结果表明，该方法对群体流动性等级分类的准确率达到99.5%，对群体结构的识别准确率达到80%左右。
Monitoring group mobility and structure is crucial for understanding group activities and social relations. In this paper, we develop algorithms for fine-grained mobility classification and structure recognition of social groups utilizing mobile devices. First, we present a method that recognizes four levels of group mobility, including stationary, strolling, walking, and running. Second, using multiple types of mobile sensors, a novel relative position relationship estimation algorithm is developed to understand different moving group structures. We have conducted real-life experiments in which 12 volunteers moved in different small groups either in an office building or a shopping mall with various speeds and structures. Experimental results show that our approach achieves an accuracy of 99.5 percent in group mobility level classification and about 80 percent in group structure recognition.