Authors:
Tobias Bolten
1
;
Regina Pohle-Fröhlich
1
;
Dorothee Volker
2
;
Clemens Brück
2
;
Nicolas Beucker
2
and
Hans-Günter Hirsch
1
Affiliations:
1
Institute of Pattern Recognition, Niederrhein University of Applied Sciences, Reinarzstr. 49, Krefeld, Germany
;
2
Competence Center for Social Urban Design, Niederrhein University of Applied Sciences, Frankenring 20, Krefeld, Germany
Keyword(s):
Activity Visualization, Heat Map, Long-Term Monitoring, Dynamic Vision Sensor.
Abstract:
In the context of urban planning, a detailed knowledge of the considered space and its utilization is essential. However, manual observations are often not performed due to cost. Whereas sensor-based systems are often not installed due to possible constrains caused by data protection laws and user privacy-concerns. We addressed these concerns and developed a privacy-aware, sensor-based processing pipeline for detecting objects based on an analysis of signals from several sensors. These detections are used for their mapping and visualization in a global bird eye view. Besides a data normalization, which is crucial considering sections of different lengths, multiple variations of activity visualization applying heat maps are described. This includes the utilization of background representations with different levels of details, different accumulations of object detections through the adjustment of the performed spatial binning as well as applying different colormaps. Both sequential co
lormaps and diverging colormaps with and without perceptually uniform distances were considered. These variations were evaluated in a conducted online survey addressing professional urban planners as well as interested citizens. The results of this survey were used to determine a meaningful default setup for visualizing the activities in an interactive graphical user interface. This interface is intended to make the results of the performed long-term monitoring generally accessible.
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