Aftab, W., Hostettler, R., De Freitas, A. et al. (2 more authors) (2019) Spatio-temporal Gaussian process models for extended and group object tracking with irregular shapes. IEEE Transactions on Vehicular Technology, 68 (3). pp. 2137-2151. ISSN 0018-9545
Abstract
Extended object tracking has become an integral part of many autonomous systems during the last two decades. For the first time, this paper presents a generic spatio-temporal Gaussian process (STGP) for tracking an irregular and non-rigid extended object. The complex shape is represented by key points and their parameters are estimated both in space and time. This is achieved by a factorization of the power spectral density function of the STGP covariance function. A new form of the temporal covariance kernel is derived with the theoretical expression of the filter likelihood function. Solutions to both the filtering and the smoothing problems are presented. A thorough evaluation of the performance in a simulated environment shows that the proposed STGP approach outperforms the state-of-the-art approach, with up to 90% improvement in the accuracy in position, 95% in velocity and 7% in the shape, while tracking a simulated asymmetric non-rigid object. The tracking performance improvement for a non-rigid irregular real object is up to 43% in position, 68% in velocity, 10% in the recall and 115% in the precision measures.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Extended object tracking; Spatio-temporal Gaussian process; Rauch-Tung-Streibel Smoother |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 688082 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 09 Jan 2019 09:32 |
Last Modified: | 25 Nov 2021 08:21 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/TVT.2019.2891006 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:140444 |