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ISPRS Int. J. Geo-Inf. 2015, 4(2), 974-988; doi:10.3390/ijgi4020974

Routing in Dense Human Crowds Using Smartphone Movement Data and Optical Aerial Imagery

1
Institute for Geoinformatics and Remote Sensing (IGF), University of Osnabrueck, Barbarastr. 22b, 49076 Osnabrueck, Germany
2
Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, 82234 Wessling, Germany
3
Institute of Geography, GIScience, Heidelberg University, Berliner Str. 48, 69120 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Stephan Winter, Alper Yilmaz, Monika Sester and Wolfgang Kainz
Received: 14 January 2015 / Accepted: 4 June 2015 / Published: 12 June 2015
(This article belongs to the Special Issue Selected Papers from the ISPRS Tracking and Imaging Challenge 2014)
View Full-Text   |   Download PDF [1475 KB, uploaded 12 June 2015]   |  

Abstract

In this paper, we propose a navigation approach for smartphones that enables visitors of major events to avoid crowded areas or narrow streets and to navigate out of dense crowds quickly. Two types of sensor data are integrated. Real-time optical images acquired and transmitted by an airborne camera system are used to compute an estimation of a crowd density map. For this purpose, a patch-based approach with a Gabor filter bank for texture classification in combination with an interest point detector and a smoothing function is applied. Furthermore, the crowd density is estimated based on location and movement speed of in situ smartphone measurements. This information allows for the enhancement of the overall crowd density layer. The composed density information is input to a least-cost routing workflow. Two possible use cases are presented, namely (i) an emergency application and (ii) a basic routing application. A prototypical implementation of the system is conducted as proof of concept. Our approach is capable of increasing the security level for major events. Visitors are able to avoid dense crowds by routing around them, while security and rescue forces are able to find the fastest way into the crowd. View Full-Text
Keywords: geo-information fusion; aerial images; smartphone trajectories; texture classification; Gabor filter; texture classification; least-cost routing geo-information fusion; aerial images; smartphone trajectories; texture classification; Gabor filter; texture classification; least-cost routing
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Hillen, F.; Meynberg, O.; Höfle, B. Routing in Dense Human Crowds Using Smartphone Movement Data and Optical Aerial Imagery. ISPRS Int. J. Geo-Inf. 2015, 4, 974-988.

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