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Human Tracking in Occlusion based on Reappearance Event Estimation
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-5863-0748
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0003-3498-0783
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
2016 (English)In: ICINCO 2016: 13th International Conference on Informatics in Control, Automation and Robotics: Proceedings, Volume 2 / [ed] Oleg Gusikhin, Dimitri Peaucelle & Kurosh Madani, SciTePress, 2016, Vol. 2, p. 505-512Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
SciTePress, 2016. Vol. 2, p. 505-512
Keywords [en]
Detection and Tracking Moving Objects, Extended Kalman Filter, Human Tracking, Occlusion, Intelligent Vehicles, Mobile Robots
National Category
Robotics Signal Processing Computer Vision and Robotics (Autonomous Systems) Medical Image Processing
Identifiers
URN: urn:nbn:se:hh:diva-31709DOI: 10.5220/0006006805050512ISI: 000392601900061Scopus ID: 2-s2.0-85013059501ISBN: 978-989-758-198-4 (electronic)OAI: oai:DiVA.org:hh-31709DiVA, id: diva2:950977
Conference
13th International Conference on Informatics in Control, Automation and Robotics, Lisbon, Portugal, 29-31 July, 2016
Available from: 2016-08-04 Created: 2016-08-04 Last updated: 2022-07-06Bibliographically approved

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Mashad Nemati, HassanGholami Shahbandi, SaeedÅstrand, Björn

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