Multi-view Onboard Clustering of Skeleton Data for Fall Risk Discovery

Takayama, Daisuke; Deguchi, Yutaka; Takano, Shigeru; Scuturici, Vasile Marian; Petit, J. M.; Suzuki, Einoshin

doi:10.1007/978-3-319-14112-1_21

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…An example in the clustering corresponds to a skeleton. The clustering method, which is based on BIRCH [17], is reported in detail in [5,15] and is out of the scope of this paper.…”

Section: System Overviewmentioning

confidence: 99%

“…For instance, a monitoring robot would greatly benefit from the ability to analyze its observations and discover patterns to adapt to its target person. With this motivation in our mind, we proposed several autonomous mobile robots which perform online clustering to discover useful patterns [13,14,15]. However, to construct such an application system with these mobile robots, we have to overcome the obstacles of developing, managing, and controlling various components.…”

Section: Introductionmentioning

confidence: 99%

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Multiple-robot monitoring system based on a service-oriented DBMS

Deguchi

Takayama

Takano

et al. 2014

Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments

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In this paper, we present a human-targeted monitoring system composed of two autonomous mobile robots based on a service-oriented DBMS, mainly from the viewpoint of positioning control. Each robot is equipped with a Kinect and monitors the target human from appropriate angles and distances. The service-oriented DBMS, which manages the monitoring system and enables a rapid development and extension of the system, views each robot as a data source which generates a data stream to be stored and processed in the DBMS. The results of the experiments conducted in a real office are promising.

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“…An example in the clustering corresponds to a skeleton. The clustering method, which is based on BIRCH [17], is reported in detail in [5,15] and is out of the scope of this paper.…”

Section: System Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%