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Tracking and following pedestrian trajectories, an approach for autonomous surveillance of critical infrastructures

机译:跟踪和跟踪行人的轨迹,这是一种自动监视关键基础设施的方法

摘要

© Emerald Group Publishing Limited [ISSN 0143-991X]. Purpose This paper aims to present a system that is fully capable of addressing the issue of detection, tracking and following pedestrians, which is a very challenging task, especially when it is considered for using in large outdoors infrastructures. Three modules, detection, tracking and following, are integrated and tested over long distances in semi-structured scenarios, where static or dynamic obstacles, including other pedestrians, can be found. Design/methodology/approach The detection is based on the probabilistic fusion of a laser scanner and a camera. The tracking module pairs observations with previously detected targets by using Kalman Filters and a Mahalanobis-distance. The following module allows to safely pursue the target by using a well-defined navigation scheme. Findings The system can track pedestrians from static position to 3.46 m/s (running). It handles occlusions, crossings or miss-detections, keeping track of the position even if the pedestrian is only detected in 55/per cent of the observations. Moreover, it autonomously selects and follows a target at a maximum speed of 1.46 m/s. Originality/value The main novelty of this study is the integration of the three algorithms in a fully operational system, tested in real outdoor scenarios. Furthermore, the addition of labelling to the detection algorithm allows using the full range of a single sensor while preserving the high performance of a combined detection. False-positives rate is reduced by handling the uncertainty level when pairing observations. The inclusion of pedestrian speed in the model speeds up and simplifies tracking process. Finally, the most suitable target is automatically selected by a scoring system.
机译:©翡翠集团出版有限公司[ISSN 0143-991X]。目的本文旨在提出一种完全能够解决检测,跟踪和跟踪行人问题的系统,这是一项非常艰巨的任务,尤其是在考虑将其用于大型户外基础设施中时。在半结构化场景中可以长距离集成和测试三个模块(检测,跟踪和跟随),在该场景中可以找到包括其他行人在内的静态或动态障碍物。设计/方法/方法检测基于激光扫描仪和照相机的概率融合。跟踪模块通过使用卡尔曼滤波器和马氏距离将观测值与先前检测到的目标配对。以下模块允许使用定义明确的导航方案安全地追踪目标。结果系统可以从静态位置跟踪行人到3.46 m / s(行驶)。它可以处理遮挡,交叉或误检,即使只有55%的观测结果中检测到行人,也可以跟踪位置。此外,它以1.46 m / s的最大速度自主选择并跟随目标。独创性/价值这项研究的主要新颖之处在于将这三种算法集成在一个完全可操作的系统中,并在室外实际场景中进行了测试。此外,在检测算法上添加标签可以在保持组合检测的高性能的同时使用单个传感器的全部范围。配对观察值时,通过处理不确定性水平,可以降低假阳性率。在模型中包含行人速度可以加快并简化跟踪过程。最后,最合适的目标由计分系统自动选择。

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