文章基本信息

标题：UNSUPERVISED GROUPING OF MOVING OBJECTS BASED ON AGGLOMERATIVE HIERARCHICAL CLUSTERING
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作者：Kaori Fujinami
期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2016
卷号：9
期号：4
页码：2276-2296
出版社：Massey University
摘要：In this article, we present a method to identify a grouping of sensor nodes that show similarmovement patterns in an ad-hoc manner. The motivation behind the ad-hoc grouping is to allow asystem to monitor complex and concrete situations of people and/or devices such as “who is/areutilizing what object(s)” and “what objects are carried together” without any supervision of humanbefore and at the time of interaction. An agglomerative hierarchical clustering algorithm was applied toa data stream to find the group members as a set of clusters within a certain height. A threshold wasalso determined in an unsupervised way based on simple statistics obtained from the previous clusteringresults. An off-line analysis was conducted on data collected in realistic situations. Although groupingtwo of the same but unrelated activities proved to be difficult, the proposed algorithm performed well inother relaxed cases such as walking with a bag vs. pushing a platform hand truck. Furthermore, weconfirmed the effectiveness of clustering-based grouping in comparison with simple distance-basedgrouping.
关键词：Smart Objects; Agglomerative Hierarchical Clustering; Grouping; Accelerometer