3D people surveillance on range data sequences of a rotating Lidar

被引:33
作者
Benedek, Csaba [1 ]
机构
[1] Hungarian Acad Sci, Inst Comp Sci & Control, Distributed Events Anal Res Lab, H-1111 Budapest, Hungary
关键词
Rotating multi-beam Lidar; MRF; Motion segmentation; Re-identification; MODEL;
D O I
10.1016/j.patrec.2014.04.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose an approach on real-time 3D people surveillance, with probabilistic foreground modeling, multiple person tracking and on-line re-identification. Our principal aim is to demonstrate the capabilities of a special range sensor, called rotating multi-beam (RMB) Lidar, as a future possible surveillance camera. We present methodological contributions in two key issues. First, we introduce a hybrid 2D-3D method for robust foreground-background classification of the recorded RMB-Lidar point clouds, with eliminating spurious effects resulted by quantification error of the discretized view angle, non-linear position corrections of sensor calibration, and background flickering, in particularly due to motion of vegetation. Second, we propose a real-time method for moving pedestrian detection and tracking in RMB-Lidar sequences of dense surveillance scenarios, with short- and long-term object assignment. We introduce a novel person re-identification algorithm based on solely the Lidar measurements, utilizing in parallel the range and the intensity channels of the sensor, which provide biometric features. Quantitative evaluation is performed on seven outdoor Lidar sequences containing various multi-target scenarios displaying challenging outdoor conditions with low point density and multiple occlusions. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:149 / 158
页数:10
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