9 June 2014 Algorithm for detecting important changes in lidar point clouds
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Protection of installations in hostile environments is a very critical part of military and civilian operations that requires a significant amount of security personnel to be deployed around the clock. Any electronic change detection system for detection of threats must have high probability of detection and low false alarm rates to be useful in the presence of natural motion of trees and vegetation due to wind. We propose a 3D change detection system based on a LIDAR sensor that can reliably and robustly detect threats and intrusions in different environments including surrounding trees, vegetation, and other natural landscape features. Our LIDAR processing algorithm finds human activity and human-caused changes not only in open spaces but also in heavy vegetated areas hidden from direct observation by 2D imaging sensors. The algorithm processes a sequence of point clouds called frames. Every 3D frame is mapped into a 2D horizontal rectangular grid. Each cell of this grid is processed to calculate the distribution of the points mapped into it. The spatial differences are detected by analyzing the differences in distributions of the corresponding cells that belong to different frames. Several heuristic filters are considered to reduce false detections caused by natural changes in the environment.
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Dmitriy Korchev, Dmitriy Korchev, Yuri Owechko, Yuri Owechko, "Algorithm for detecting important changes in lidar point clouds", Proc. SPIE 9080, Laser Radar Technology and Applications XIX; and Atmospheric Propagation XI, 90800N (9 June 2014); doi: 10.1117/12.2050926; https://doi.org/10.1117/12.2050926

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