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. 2017 Oct 20;17(10):2391.
doi: 10.3390/s17102391.

An Improved Indoor Positioning System Using RGB-D Cameras and Wireless Networks for Use in Complex Environments

Jaime Duque Domingo  1 , Carlos Cerrada  2 , Enrique Valero  3 , Jose A Cerrada  4
Affiliations

An Improved Indoor Positioning System Using RGB-D Cameras and Wireless Networks for Use in Complex Environments

Jaime Duque Domingo et al. Sensors (Basel). .

Abstract

This work presents an Indoor Positioning System to estimate the location of people navigating in complex indoor environments. The developed technique combines WiFi Positioning Systems and depth maps, delivering promising results in complex inhabited environments, consisting of various connected rooms, where people are freely moving. This is a non-intrusive system in which personal information about subjects is not needed and, although RGB-D cameras are installed in the sensing area, users are only required to carry their smart-phones. In this article, the methods developed to combine the above-mentioned technologies and the experiments performed to test the system are detailed. The obtained results show a significant improvement in terms of accuracy and performance with respect to previous WiFi-based solutions as well as an extension in the range of operation.

Keywords: IPS; Kinect; RGB-D sensors; WPS; WiFi; depth map; fingerprinting; indoor positioning; skeletons; trajectory.

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Conflict of interest statement

The authors declare that there is no conflict of interest regarding the publication of this manuscript.

Figures

Figure 1
Figure 1
Scenario of the system.
Figure 2
Figure 2
Activity diagram during the Training stage.
Figure 3
Figure 3
Activity diagram during the Operational stage.
Figure 4
Figure 4
Scheme of web service callings.
Figure 5
Figure 5
Cells with WPS and skeleton trajectories during the Operational stage.
Figure 6
Figure 6
Kinect sensor mounted on a platform.
Figure 7
Figure 7
Plan of the office used in the experiments.
Figure 8
Figure 8
Screenshot of the application developed for Android devices.
Figure 9
Figure 9
Some of the trajectories followed by users.
Figure 10
Figure 10
Positioning success (%) for a different number of users and time stamps.
See this image and copyright information in PMC

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