Tracking of People in Paper Mill Warehouse Using Laser Range Sensor

Nemati, Hassan Mashad; Åstrand, Björn

doi:10.1109/ems.2014.39

Cited by 3 publications

(1 citation statement)

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“…Some approaches are based on 2D and 3D laser scanners (Castro et al, 2004), (Xavier et al, 2005), (Arras et al, 2007), (Nemati andÅstrand, 2014), (Lovas and Barsi, 2015), visual sensors and cameras (Papageorgiou and Poggio, 2000), (Dalal and Triggs, 2005), (Tuzel et al, 2007), (Schiele et al, 2009), (Zitouni et al, 2015), or a combination of both laser scanners and visual sensors (Zivkovic and Krose, 2007), (Arras and Mozos, 2009), (Linder and Arras, 2016).…”

Section: Introductionmentioning

confidence: 99%

Human Tracking in Occlusion based on Reappearance Event Estimation

Nemati

Shahbandi

Åstrand

2016

Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

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Abstract:Relying on the commonsense knowledge that the trajectory of any physical entity in the spatio-temporal domain is continuous, we propose a heuristic data association technique. The technique is used in conjunction with an Extended Kalman Filter (EKF) for human tracking under occlusion. Our method is capable of tracking moving objects, maintain their state hypothesis even in the period of occlusion, and associate the target reappeared from occlusion with the existing hypothesis. The technique relies on the estimation of the reappearance event both in time and location, accompanied with an alert signal that would enable more intelligent behavior (e.g. in path planning). We implemented the proposed method, and evaluated its performance with real-world data. The result validates the expected capabilities, even in case of tracking multiple humans simultaneously.

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