Open AccessPEDESTRIAN DETECTION BY LASER SCANNING AND DEPTH IMAGERY
Author(s) -
A. Barsi,
T. Lovas,
Balázs Molnár,
A. Somogyi,
Z. Igazvolgyi
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b3-465-2016
Subject(s) - point cloud , pedestrian , laser scanning , computer science , computer vision , artificial intelligence , point (geometry) , volume (thermodynamics) , laser , computer graphics (images) , engineering , transport engineering , mathematics , optics , physics , geometry , quantum mechanics
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).