PEDESTRIAN DETECTION BY LASER SCANNING AND DEPTH IMAGERY
Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements without disturbing and changing...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/465/2016/isprs-archives-XLI-B3-465-2016.pdf |
| Summary: | Pedestrian flow is much less regulated and controlled compared to vehicle traffic. Estimating flow parameters would support many
safety, security or commercial applications. Current paper discusses a method that enables acquiring information on pedestrian movements
without disturbing and changing their motion. Profile laser scanner and depth camera have been applied to capture the geometry
of the moving people as time series. Procedures have been developed to derive complex flow parameters, such as count, volume,
walking direction and velocity from laser scanned point clouds. Since no images are captured from the faces of pedestrians, no privacy
issues raised. The paper includes accuracy analysis of the estimated parameters based on video footage as reference. Due to the
dense point clouds, detailed geometry analysis has been conducted to obtain the height and shoulder width of pedestrians and to detect
whether luggage has been carried or not. The derived parameters support safety (e.g. detecting critical pedestrian density in mass
events), security (e.g. detecting prohibited baggage in endangered areas) and commercial applications (e.g. counting pedestrians at all
entrances/exits of a shopping mall). |
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| ISSN: | 1682-1750 2194-9034 |